WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web
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paper_title: Bespoke Physics for Living Technology

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In the physics of the natural world, basic tasks of life, such as homeostasis and reproduction, are extremely complex operations, requiring the coordination of billions of atoms even in simple cases. By contrast, artificial living organisms can be implemented in computers using relatively few bits, and copying a data structure is trivial. Of course, the physical overheads of the computers themselves are huge, but since their programmability allows digital "laws of physics" to be tailored like a custom suit, deploying living technology atop an engineered computational substrate might be as or more effective than building directly on the natural laws of physics, for a substantial range of desirable purposes. This article suggests basic criteria and metrics for bespoke physics computing architectures, describes one such architecture, and offers data and illustrations of custom living technology competing to reproduce while collaborating on an externally useful computation.
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paper_title: Real artificial life: Where we may be

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Artificial life research typically employs digital computers to implement models of living systems. However, there is now a growing if pro-theoretical feeling that computers, or perhaps the software running on them, are themselves some kind of living systems. Such a possibility can impact artificial life research in at least two ways By highlighting that computers and comnnunications networks can be subjects, as well as tools, for artificial life muodelling, and by highlighting that insights, tools, and models from the life sciences can have explanatory, predictive, and design consequences for the construction of future computation and communications systems. This paper seeks perspective on such ‘real artificial life’, looking backwards and forwards at the rise of living systems in manufactured computer and communications systems
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paper_title: Artificial life programming in the robust-first attractor

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Despite mounting awareness of the liabilities of deterministic CPU and RAM computing, across industry and academia there remains little clear vision of a fundamental, generalpurpose alternative. To obtain indefinitely scalable computer architectures offering improved robustness and security, we have advocated a realignment of the roles of hardware and software based on artificial life principles. In this paper we propose an active media computational abstraction to underlie such a hardware-software renegotiation. The active media framework is much in the spirit of probabilistic cellular automata, but designed for indefinite scalability and serious programmability, rather than simplicity and analytic tractability. We discuss active media programming techniques based on living systems principles, and present anecdotal data from sample programs to introduce a new programming language called ulam, that we are developing as an underlying language for active media.
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paper_title: Galaxy Zoo : Morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey

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In order to understand the formation and subsequent evolution of galaxies one must first distinguish between the two main morphological classes of massive systems: spirals and early-type systems. This paper introduces a project, Galaxy Zoo, which provides visual morphological classifications for nearly one million galaxies, extracted from the Sloan Digital Sky Survey (SDSS). This achievement was made possible by inviting the general public to visually inspect and classify these galaxies via the internet. The project has obtained more than 4 × 107 individual classifications made by ∼105 participants. We discuss the motivation and strategy for this project, and detail how the classifications were performed and processed. We find that Galaxy Zoo results are consistent with those for subsets of SDSS galaxies classified by professional astronomers, thus demonstrating that our data provide a robust morphological catalogue. Obtaining morphologies by direct visual inspection avoids introducing biases associated with proxies for morphology such as colour, concentration or structural parameters. In addition, this catalogue can be used to directly compare SDSS morphologies with older data sets. The colour–magnitude diagrams for each morphological class are shown, and we illustrate how these distributions differ from those inferred using colour alone as a proxy for morphology.
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paper_title: Automated Evolution of Interesting Images

paper_content:

Note: The Humanities and ALife -- Best Presentation Award Winner. Reference EPFL-CONF-191282 Record created on 2013-12-13, modified on 2017-05-10
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paper_title: The Art of Computer Virus Research and Defense

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"Of all the computer-related books I've read recently, this one influenced my thoughts about security the most. There is very little trustworthy information about computer viruses. Peter Szor is one of the best virus analysts in the world and has the perfect credentials to write this book."-Halvar Flake, Reverse Engineer, SABRE Security GmbHSymantec's chief antivirus researcher has written the definitive guide to contemporary virus threats, defense techniques, and analysis tools. Unlike most books on computer viruses, The Art of Computer Virus Research and Defense is a reference written strictly for white hats: IT and security professionals responsible for protecting their organizations against malware. Peter Szor systematically covers everything you need to know, including virus behavior and classification, protection strategies, antivirus and worm-blocking techniques, and much more.Szor presents the state-of-the-art in both malware and protection, providing the full technical detail that professionals need to handle increasingly complex attacks. Along the way, he provides extensive information on code metamorphism and other emerging techniques, so you can anticipate and prepare for future threats.Szor also offers the most thorough and practical primer on virus analysis ever published-addressing everything from creating your own personal laboratory to automating the analysis process. This book's coverage includes Discovering how malicious code attacks on a variety of platforms Classifying malware strategies for infection, in-memory operation, self-protection, payload delivery, exploitation, and more Identifying and responding to code obfuscation threats: encrypted, polymorphic, and metamorphic Mastering empirical methods for analyzing malicious code-and what to do with what you learn Reverse-engineering malicious code with disassemblers, debuggers, emulators, and virtual machines Implementing technical defenses: scanning, code emulation, disinfection, inoculation, integrity checking, sandboxing, honeypots, behavior blocking, and much more Using worm blocking, host-based intrusion prevention, and network-level defense strategies © Copyright Pearson Education. All rights reserved.
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paper_title: Crystal structure of a monomeric retroviral protease solved by protein folding game players

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Following the failure of a wide range of attempts to solve the crystal structure of M-PMV retroviral protease by molecular replacement, we challenged players of the protein folding game Foldit to produce accurate models of the protein. Remarkably, Foldit players were able to generate models of sufficient quality for successful molecular replacement and subsequent structure determination. The refined structure provides new insights for the design of antiretroviral drugs.
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paper_title: Computer Viruses as Artificial Life

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There has been considerable interest in computer viruses since they first appeared in 1981, and especially in the past few years as they have reached epidemic numbers in many personal computer environments. Viruses have been written about as a security problem, as a social problem, and as a possible means of performing useful tasks in a distributed computing environment. However, only recently have some scientists begun to ask if computer viruses are not a form of artificial life—a self-replicating organism. Simply because computer viruses do not exist as organic molecules may not be sufficient reason to dismiss the classification of this form of vandalware as a form of life. This paper begins with a description of how computer viruses operate and their history, and of the various ways computer viruses are structured. It then examines how viruses meet properties associated with life as defined by some researchers in the area of artificial life and self-organizing systems. The paper concludes with some comments directed toward the definition of artificially alive systems and experimentation.
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paper_title: Development and Evolution of Neural Networks in an Artificial Chemistry

paper_content:

We present a model of decentralized growth for Artificial Neural Networks (ANNs) inspired by the development and the physiology of real nervous systems. In this model, each individual artificial neuron is an autonomous unit whose behavior is determined only by the genetic information it harbors and local concentrations of substrates modeled by a simple artificial chemistry. Gene expression is manifested as axon and dendrite growth, cell division and differentiation, substrate production and cell stimulation. We demonstrate the model's power with a hand-written genome that leads to the growth of a simple network which performs classical conditioning. To evolve more complex structures, we implemented a platform-independent, asynchronous, distributed Genetic Algorithm (GA) that allows users to participate in evolutionary experiments via the World Wide Web.
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paper_title: A Developmental Model for the Evolution of Artificial Neural Networks

paper_content:

We present a model of decentralized growth and development for artificial neural networks (ANNs), inspired by developmental biology and the physiology of nervous systems. In this model, each individual artificial neuron is an autonomous unit whose behavior is determined only by the genetic information it harbors and local concentrations of substrates. The chemicals and substrates, in turn, are modeled by a simple artificial chemistry. While the system is designed to allow for the evolution of complex networks, we demonstrate the power of the artificial chemistry by analyzing engineered (handwritten) genomes that lead to the growth of simple networks with behaviors known from physiology. To evolve more complex structures, a Java-based, platform-independent, asynchronous, distributed genetic algorithm (GA) has been implemented that allows users to participate in evolutionary experiments via the World Wide Web.
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paper_title: RoboGen: Robot Generation through Artificial Evolution

paper_content:

Science instructors from a wide range of disciplines agree that hands-on laboratory components of courses are pedagogically necessary (Freedman, 1997). However, certain shortcomings of current laboratory exercises have been pointed out by several authors (Mataric, 2004; Hofstein and Lunetta, 2004). The overarching theme of these analyses is that hands-on components of courses tend to be formulaic, closed-ended, and at times outdated. To address these issues, we envision a novel platform that is not only a didactic tool but is also an experimental testbed for users to play with different ideas in evolutionary robotics (Nolfi and Floreano, 2000), neural networks, physical simulation, 3D printing, mechanical assembly, and embedded processing. Here, we introduce RoboGen™: an open-source software and hardware platform designed for the joint evolution of robot morphologies and controllers a la Sims (1994); Lipson and Pollack (2000); Bongard and Pfeifer (2003). Robo- Gen has been designed specifically to allow evolved robots to be easily manufactured via widely available desktop 3D-printers, and the use of simple, open-source, low-cost, offthe- shelf electronic components. RoboGen features an evolution engine complete with a physics simulator, as well as utilities both for generating design files of body components for 3D printing, and for compiling neural-network controllers to run on an Arduino microcontroller board.
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paper_title: Evolving 3d morphology and behavior by competition

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This article describes a system for the evolution and coevolution of virtual creatures that compete in physically simulated three-dimensional worlds. Pairs of individuals enter one-on-one contests in which they contend to gain control of a common resource. The winners receive higher relative fitness scores allowing them to survive and reproduce. Realistic dynamics simulation including gravity, collisions, and friction, restricts the actions to physically plausible behaviors. ::: ::: The morphology of these creatures and the neural systems for controlling their muscle forces are both genetically determined, and the morphology and behavior can adapt to each other as they evolve simultaneously. The genotypes are structured as directed graphs of nodes and connections, and they can efficiently but flexibly describe instructions for the development of creatures' bodies and control systems with repeating or recursive components. When simulated evolutions are performed with populations of competing creatures, interesting and diverse strategies and counterstrategies emerge.
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paper_title: SETI@home: an experiment in public-resource computing

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Millions of computer owners worldwide contribute computer time to the search for extraterrestrial intelligence, performing the largest computation ever.
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paper_title: The EvoGrid - A Framework for Distributed Artificial Chemistry Cameo Simulations Supporting Computational Origins of Life Endeavors

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The Evolution Grid, or EvoGrid is a computer simulation framework for distributed artificial chemistry (AC) supp orting computational origins of life (COoL) research. The EvoGrid consists of a number of small experiments running on sho rt time scales pruned by aggressive tree-branching search es supported by random parametric re-seeding and temporal backtracking. The EvoGrid is designed to converge upon the observation of “cameo” simulations of key pre-biotic or simple biological structures or behaviors. These cameo simula tions can then inform and feed larger AC simulations operating over biologically relevant time scales. In addition, the framework is designed to plug into a heterogeneous set of engines ranging from high fidelity molecular dynamics (MD) to more abstract AC techniques on the same set of data. The EvoGrid a lso provides shared web-based simulation management services and uniform, open standards for execution, storage an d data analysis. We conclude by describing the first prototype implementation of the EvoGrid, early results, next ste ps and open questions in this and other COoL endeavors.
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paper_title: Service oriented evolutionary algorithms

paper_content:

This work presents a service oriented architecture for evolutionary algorithms, and an implementation of this architecture using a specific technology (called OSGiLiath). Service oriented architecture is a computational paradigm where users interact using services to increase the integration between systems. The presented abstract architecture is formed by loosely coupled, highly configurable and language-independent services. As an example of an implementation of this architecture, a complete process development using a specific service oriented technology is explained. With this implementation, less effort than classical development in integration, distribution mechanisms and execution time management has been attained. In addition, steps, ideas, advantages and disadvantages, and guidelines to create service oriented evolutionary algorithms are presented. Using existing software, or from scratch, researchers can create services to increase the interoperability in this area.
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paper_title: Task-switching costs promote the evolution of division of labor and shifts in individuality

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From microbes to humans, the success of many organisms is achieved by dividing tasks among specialized group members. The evolution of such division of labor strategies is an important aspect of the major transitions in evolution. As such, identifying specific evolutionary pressures that give rise to group-level division of labor has become a topic of major interest among biologists. To overcome the challenges associated with studying this topic in natural systems, we use actively evolving populations of digital organisms, which provide a unique perspective on the de novo evolution of division of labor in an open-ended system. We provide experimental results that address a fundamental question regarding these selective pressures: Does the ability to improve group efficiency through the reduction of task-switching costs promote the evolution of division of labor? Our results demonstrate that as task-switching costs rise, groups increasingly evolve division of labor strategies. We analyze the mechanisms by which organisms coordinate their roles and discover strategies with striking biological parallels, including communication, spatial patterning, and task-partitioning behaviors. In many cases, under high task-switching costs, individuals cease to be able to perform tasks in isolation, instead requiring the context of other group members. The simultaneous loss of functionality at a lower level and emergence of new functionality at a higher level indicates that task-switching costs may drive both the evolution of division of labor and also the loss of lower-level autonomy, which are both key components of major transitions in evolution.
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paper_title: Artificial Life Applied to Adaptive Information Agents

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We propose a model, inspired by recent artificial life theory, applied to the problem of retrieving information from a large, distributed collection of documents such as the World Wide Web. A population of agents is evolved under density dependent selection for the task of locating information for the user. The energy necessary for survival is obtained from both environment and user in exchange for appropriate information. By competing for relevant documents, the agents robustly adapt to their information environment and are allocated to efficiently exploit shared resources. We illustrate the roles played by document locality, adaptive search strategies, and relevance feedback, in the information gathering process.
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paper_title: VERBARIUM and LIFE SPACIES: creating a visual language by transcoding text into form on the Internet

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We are artists working on the creation of interactive computer systems that use the audiences' participation as essential input for the creation of image structures. In 1998 and 1999 we created two interactive Web sites for the Internet called VERBARIUM and LIFE SPACIES. These two Web sites allow users on the Internet to write text messages that are instantly translated into visual 3D forms. Our custom designed text-to-form editor takes the letters, syntax and sequencing of a text message as generic code and updates the design functions for the creation of 3D forms according to the text message parameters. As the text messages of the different users on the Internet are usually unique and diverse, unique and personal 3D visual forms and shapes can be created by the users.
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paper_title: Symbiotic Intelligence: Self-organizing knowledge on distributed networks driven by human interactions

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This work addresses how human societies, and other diverse and distributed systems, solve collective challenges that are not approachable from the level of the individual, and how the Internet will change the way societies and organizations view problem solving. The authors apply the ideas developed in self-organizing systems to understand self-organization in informational systems. The simplest explanation as to why animals (for example, ants, wolves, and humans) are organized into societies is that these societies enhance the survival of the individuals which make up the populations. Individuals contribute to, as well as adapt to, these societies because they make life easier in one way or another, even though they may not always understand the process, either individually or collectively. Despite the lack of understanding of the how of the process, society during its existence as a species has changed significantly, from separate, small hunting tribes to a highly technological, globally integrated society. The authors combine this understanding of societal dynamics with self-organization on the Internet (the Net). The unique capability of the Net is that it combines, in a common medium, the entire human-technological system in both breadth and depth: breadth in the integration of heterogeneous systems of machines, information and people; and depth in the detailed capturing of the entire complexity of human use and creation of information. When the full diversity of societal dynamics is combined with the accuracy of communication on the Net, a phase transition is argued to occur in problem solving capability. Through conceptual examples, an experiment of collective decision making on the Net and a simulation showing the effect of noise and loss on collective decision making, the authors argue that the resulting symbiotic structure of humans and the Net will evolve as an alternative problem solving approach for groups, organizations and society. Self-organizing knowledge formation from this symbiotic intelligence exemplifies a new type of self-organizing system, one without dissipation and not constrained by limited resources.
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paper_title: Collective Learning and Semiotic Dynamics

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We report on a case study in the emergence of a lexicon in a group of autonomous distributed agents situated and grounded in an open environment. Because the agents are autonomous, grounded, and situated, the possible words and possible meanings are not fixed but continuously change as the agents autonomously evolve their communication system and adapt it to novel situations. The case study shows that a complex semiotic dynamics unfolds and that generalisations present in the language are due to processes outside the agent.
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paper_title: Evolution and Collective Intelligence of the Electric Sheep

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Electric Sheep is a collective intelligence composed of 40,000 computers and people mediated by a genetic algorithm. It is made with an open source screen-saver that harnesses idle computers into a render farm with the purpose of animating and evolving artificial life-forms known as sheep. The votes of the users form the basis for a fitness function for exploring a space of abstract animations. Users also may design sheep by hand for inclusion in the gene pool.
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paper_title: Developing e-Bug web games to teach microbiology

paper_content:

As a complement to the e-Bug teaching pack, two e-Bug games were developed to provide content that aimedto entertain as well as to educate. A set of agreed learning outcomes (LOs) were provided by the scientiﬁc part-ners of the e-Bug Project and the games were developed using user-centred design techniques (the needs,wants and limitations of the potential game players were assessed at each stage of the design process).The e-Bug games were designed for two age groups: Junior (9–12 year olds); and Senior (13–15 year olds).A study using focus groups was done to gain an understanding as to the types of games enjoyed by thetarget users. According to the preliminary study, the Junior Game was developed as a platform game andthe Senior Game was developed as a story-based detective game. The Junior Game consists of ﬁve levels,each associated with a set of LOs. Similarly, the Senior Game consists of four missions, each comprising ﬁvestages using problem-based learning techniques and LOs. In this paper, the process of development foreach game is described in detail and an illustration is provided of how each game level or mission addressesthe target LOs.Development of the games used feedback acquired from children in four schools across the UK (Glasgow,London and two in Gloucester). The children were selected according to their willingness to participate.European Partners of the e-Bug Project also provided further support, translation and requests for modiﬁ-cations. The knowledge gained of LOs and further evaluation of the games is continuing, and preliminaryresults are in press. The ﬁnal versions of the games, translated into 11 European languages, are availableonline via www.e-bug.eu.Keywords: antibiotic resistance, hand washing, education web games, Internet intervention, problem-based learning (PBL)
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paper_title: Metacreation: Art and Artificial Life

paper_content:

Artificial life, or a-life, is an interdisciplinary science focused on artificial systems that mimic the properties of living systems. In the 1990s, new media artists began appropriating and adapting the techniques of a-life science to create a-life art; Mitchell Whitelaw's Metacreation is the first detailed critical account of this new field of creative practice. A-life art responds to the increasing technologisation of living matter by creating works that seem to mutate, evolve, and respond with a life of their own. Pursuing a-life's promise of emergence, these artists produce not only artworks, but also generative and creative processes: here creation becomes metacreation. Whitelaw presents a-life art practice through four of its characteristic techniques and tendencies. "Breeders" use artificial evolution to generate images and forms, in the process altering the artist's creative agency. "Cybernatures" form complex, interactive systems, drawing the audience into artificial ecosystems. Other artists work in "Hardware," adapting Rodney Brooks's "bottom-up" robotics to create embodied autonomous agencies. The "Abstract Machines" of a-life art de-emphasise the biological analogy, using techniques such as cellular automata to investigate pattern, form and morphogenesis. In the book's concluding chapters Whitelaw surveys the theoretical discourses around a-life art, before finally examining emergence, a concept central to a-life, and key, it is argued, to a-life art.
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paper_title: Flocks, herds and schools: A distributed behavioral model

paper_content:

The aggregate motion of a flock of birds, a herd of land animals, or a school of fish is a beautiful and familiar part of the natural world. But this type of complex motion is rarely seen in computer animation. This paper explores an approach based on simulation as an alternative to scripting the paths of each bird individually. The simulated flock is an elaboration of a particle systems, with the simulated birds being the particles. The aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose their own course. Each simulated bird is implemented as an independent actor that navigates according to its local perception of the dynamic environment, the laws of simulated physics that rule its motion, and a set of behaviors programmed into it by the "animator." The aggregate motion of the simulated flock is the result of the dense interaction of the relatively simple behaviors of the individual simulated birds.
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paper_title: Nerve garden: germinating biological metaphors in net‐based virtual worlds

paper_content:

Nerve Garden is a biologically‐inspired multi‐user collaborative 3D virtual world available to a wide Internet audience. The project combines a number of methods and technologies, including L‐systems, Java, cellular automata, and virtual reality modeling language. Nerve Garden is a work in progress designed to provide a compelling experience of a virtual terrarium which exhibits properties of growth, decay and energy transfer reminiscent of a simple ecosystem. The goals of the Nerve Garden project are to create an on‐line “collaborative artificial life laboratory” which can be extended by a large number of users for purposes of education and research.
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paper_title: Living Technology: Exploiting Life's Principles in Technology

paper_content:

The concept of living technology---that is, technology that is based on the powerful core features of life---is explained and illustrated with examples from artificial life software, reconfigurable and evolvable hardware, autonomously self-reproducing robots, chemical protocells, and hybrid electronic-chemical systems. We define primary (secondary) living technology according as key material components and core systems are not (are) derived from living organisms. Primary living technology is currently emerging, distinctive, and potentially powerful, motivating this review. We trace living technology's connections with artificial life (soft, hard, and wet), synthetic biology (top-down and bottom-up), and the convergence of nano-, bio-, information, and cognitive (NBIC) technologies. We end with a brief look at the social and ethical questions generated by the prospect of living technology.
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paper_title: ImageNet: A large-scale hierarchical image database

paper_content:

The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images and multimedia data. But exactly how such data can be harnessed and organized remains a critical problem. We introduce here a new database called “ImageNet”, a large-scale ontology of images built upon the backbone of the WordNet structure. ImageNet aims to populate the majority of the 80,000 synsets of WordNet with an average of 500-1000 clean and full resolution images. This will result in tens of millions of annotated images organized by the semantic hierarchy of WordNet. This paper offers a detailed analysis of ImageNet in its current state: 12 subtrees with 5247 synsets and 3.2 million images in total. We show that ImageNet is much larger in scale and diversity and much more accurate than the current image datasets. Constructing such a large-scale database is a challenging task. We describe the data collection scheme with Amazon Mechanical Turk. Lastly, we illustrate the usefulness of ImageNet through three simple applications in object recognition, image classification and automatic object clustering. We hope that the scale, accuracy, diversity and hierarchical structure of ImageNet can offer unparalleled opportunities to researchers in the computer vision community and beyond.
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paper_title: Evolving three-dimensional objects with a generative encoding inspired by developmental biology

paper_content:

This paper introduces an algorithm for evolving 3D objects with a generative encoding that abstracts how biological morphologies are produced. Evolving interesting 3D objects is useful in many disciplines, including artistic design (e.g. sculpture), engineering (e.g. robotics, architecture, or product design), and biology (e.g. for investigating morphological evolution). A critical element in evolving 3D objects is the representation, which strongly influences the types of objects produced. In 2007 a representation was introduced called Compositional Pattern Producing Networks (CPPN), which abstracts how natural phenotypes are generated. To date, however, the ability of CPPNs to create 3D objects has barely been explored. Here we present a new way to create 3D objects with CPPNs. Experiments with both interactive and target-based evolution demonstrate that CPPNs show potential in generating interesting, complex, 3D objects. We further show that changing the information provided to CPPNs and the functions allowed in their genomes biases the types of objects produced. Finally, we validate that the objects transfer well from simulation to the real-world by printing them with a 3D printer. Overall, this paper shows that evolving objects with encodings based on concepts from biological development can be a powerful way to evolve complex, interesting objects, which should be of use in fields as diverse as art, engineering, and biology. Motivation and Previous Work The diversity, complexity, and function of natural morphologies is awe-inspiring. Evolution has created bodies that can fly, run, and swim with amazing agility. It would be desirable to harness the power of evolution to create synthetic physical designs and morphologies. Doing so would benefit a variety of fields. For example, artists, architects and engineers could evolve sculptures, buildings, product designs, and sophisticated robots. Evolution should be especially helpful in the design of complex objects with many interacting parts made of non-linear materials. In such challenging problem domains, evolution excels while human intuition is limited. Being able to evolve sophisticated morphologies also furthers biological research because it enables the investigation of how and why certain natural designs were produced. Evolving 3D objects is thus worthwhile both as a Figure 1: Examples of evolved objects that were transferred to reality via a 3D printer. basic science and for its innumerable potential applications. This paper describes how 3D shapes can be evolved and then transferred to reality via 3D printing technology (Figure 1). Previous research in digital morphological evolution has typically involved encodings that were either highly biologically detailed, or highly-abstract with less biological accuracy. The former camp frequently simulates the low-level processes that govern biological development, such as the diffusing morphogen chemicals and proteins that determine the identity of embryonic cells (Bongard and Pfeifer 2001, Eggenberger 1997, Miller 2004). While this approach facilitates studying the mechanisms of developmental biology, the computational cost of simulating chemistry in such detail greatly limits the complexity of the evolved phenotypes. The most complex forms typically evolved in such systems are simple geometric patterns (such as three bands) (Miller 2004) or groups of shapes resembling the earliest stages of animal development (Eggenberger 1997). The second camp employs high-level abstractions that enable the evolution of more elaborate forms with many parts, but these abstractions tend not to reflect the way that organisms actually develop (Wolpert and Tickle 2010, Bentley 1996). An example is Lindenmayer Systems (L-Systems), which iteratively replace symbols in strings with other symbols until a termination criteria is reached (Lindenmayer 1968, Hornby et al. 2003). While L-Systems can reproduce a wide variety of organismal shapes, especially those of branching plants, they do not model plant developmental processes (Wolpert and Tickle 2010). Another example is the work of Sims (1994), who evolved morphologies that resembled some biological creatures, although with an abstract encoding based on parameterized recursion that does not resemble natural developmental processes (Sims 1994). A third option is possible, wherein a high-level abstraction is based on the developmental processes that give rise to natural forms. An example of this approach is Compositional Pattern Producing Networks (CPPNs) (Stanley 2007), which are used to evolve 3D objects in this paper and are described in Methods. Two groups have previously evolved 3D objects with CPPNs, although neither conducted an openended exploration of 3D objects. One group evolved CPPN objects that were composed of variable-sized spheres and were evaluated on two tasks: falling (Auerbach and Bongard 2010b) or moving rapidly (Auerbach and Bongard 2010a). Most of the evolved forms resembled clubs. A second group evolved soft-bodied robots to move quickly (Hiller and Lipson 2010). These studies demonstrate that CPPNs can create functional shapes, but leave open the question of what types of 3D objects CPPNs can produce with fewer constraints and without specific objectives. 2D pictures are evolved with CPPNs on picbreeder.org, where humans perform selection (Secretan et al. 2011). The complexity and natural appearance of the resulting images often support claims regarding the legitimacy of CPPNs as an abstraction of biological development (Stanley 2007). A demonstration in 3D would significantly strengthen these claims, however, because the natural world is 3D. It is possible that CPPNs are unable to frequently make sensible forms with the added difficulty of another dimension, and when objects must be one contiguous unit (which aids in transfers to reality). A recent paper by Bansagi Jr et al. (Science 2011) highlights the need to verify that generative encodings that produce complex patterns in 2D also can do so in 3D. By evolving CPPN objects in the natural 3D setting, this paper conducts a critical test of the hypothesis that generative encodings based on geometric abstractions of development capture some of the complexity-generating power of natural morphological development. Doing so also provides a visually intuitive testbed for studying how variants of such generative encodings behave. It also reveals the utility of CPPNs as a representation for 3D object design.
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paper_title: Coupled Phases and Combinatorial Selection in Fluctuating Hydrothermal Pools: A Scenario to Guide Experimental Approaches to the Origin of Cellular Life

paper_content:

Hydrothermal fields on the prebiotic Earth are candidate environments for biogenesis. We propose a model in which molecular systems driven by cycles of hydration and dehydration in such sites undergo chemical evolution in dehydrated films on mineral surfaces followed by encapsulation and combinatorial selection in a hydrated bulk phase. The dehydrated phase can consist of concentrated eutectic mixtures or multilamellar liquid crystalline matrices. Both conditions organize and concentrate potential monomers and thereby promote polymerization reactions that are driven by reduced water activity in the dehydrated phase. In the case of multilamellar lipid matrices, polymers that have been synthesized are captured in lipid vesicles upon rehydration to produce a variety of molecular systems. Each vesicle represents a protocell, an “experiment” in a natural version of combinatorial chemistry. Two kinds of selective processes can then occur. The first is a physical process in which relatively stable molecular systems will be preferentially selected. The second is a chemical process in which rare combinations of encapsulated polymers form systems capable of capturing energy and nutrients to undergo growth by catalyzed polymerization. Given continued cycling over extended time spans, such combinatorial processes will give rise to molecular systems having the fundamental properties of life.
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paper_title: EvoSpace: a distributed evolutionary platform based on the tuple space model

paper_content:

This paper presents EvoSpace, a Cloud service for the development of distributed evolutionary algorithms. EvoSpace is based on the tuple space model, an associatively addressed memory space shared by several processes. Remote clients, called EvoWorkers, connect to EvoSpace and periodically take a subset of individuals from the global population, perform evolutionary operations on them, and return a set of new individuals. Several EvoWorkers carry out the evolutionary search in parallel and asynchronously, interacting with each other through the central repository. EvoSpace is designed to be domain independent and flexible, in the sense that in can be used with different types of evolutionary algorithms and applications. In this paper, a genetic algorithm is tested on the EvoSpace platform using a well-known benchmark problem, achieving promising results compared to a standard evolutionary system.
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paper_title: Development and Evolution of Neural Networks in an Artificial Chemistry

paper_content:

We present a model of decentralized growth for Artificial Neural Networks (ANNs) inspired by the development and the physiology of real nervous systems. In this model, each individual artificial neuron is an autonomous unit whose behavior is determined only by the genetic information it harbors and local concentrations of substrates modeled by a simple artificial chemistry. Gene expression is manifested as axon and dendrite growth, cell division and differentiation, substrate production and cell stimulation. We demonstrate the model's power with a hand-written genome that leads to the growth of a simple network which performs classical conditioning. To evolve more complex structures, we implemented a platform-independent, asynchronous, distributed Genetic Algorithm (GA) that allows users to participate in evolutionary experiments via the World Wide Web.
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paper_title: A Developmental Model for the Evolution of Artificial Neural Networks

paper_content:

We present a model of decentralized growth and development for artificial neural networks (ANNs), inspired by developmental biology and the physiology of nervous systems. In this model, each individual artificial neuron is an autonomous unit whose behavior is determined only by the genetic information it harbors and local concentrations of substrates. The chemicals and substrates, in turn, are modeled by a simple artificial chemistry. While the system is designed to allow for the evolution of complex networks, we demonstrate the power of the artificial chemistry by analyzing engineered (handwritten) genomes that lead to the growth of simple networks with behaviors known from physiology. To evolve more complex structures, a Java-based, platform-independent, asynchronous, distributed genetic algorithm (GA) has been implemented that allows users to participate in evolutionary experiments via the World Wide Web.
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paper_title: ALife Meets Web: Lessons Learned

paper_content:

Artificial life might come to play important roles for the World Wide Web, both as a source of new algorithmic paradigms and as a source of inspiration for its future development. New Web searching and managing techniques, based on artificial life principles, have been elicited by the striking similarities between the Web and natural environments. New Web interface designs, based on artificial life techniques, have resulted in increased aesthetic appeal, smart animations, and clever interactive rules. In this paper we exemplify these observations by surveying a number of meeting points between artificial life and the Web. We touch on a few implementation issues and attempt to draw some lessons to be learned from these early experiences.
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paper_title: Assessing Writing in MOOCs: Automated Essay Scoring and Calibrated Peer Review™

paper_content:

Joshua Brown, Adam Mikeal, and Alysha Clark provided substantial feedback that greatly enhanced the value and clarity of the information in this article. Abstract Two of the largest Massive Open Online Course (MOOC) organizations have chosen different methods for the way they will score and provide feedback on essays students submit. EdX, MIT and Harvard’s non-profit MOOC federation, recently announced that they will use a machine-based Automated Essay Scoring (AES) application to assess written work in their MOOCs. Coursera, a Stanford startup for MOOCs, has been skeptical of AES applications and therefore has held that it will use some form of human-based “calibrated peer review” to score and provide feedback on student writing. This essay reviews the relevant literature on AES and UCLA’s Calibrated Peer ReviewTM (CPR) product at a high level, outlines the capabilities and limitations of both AES and CPR, and provides a table and framework for comparing these forms of assessment of student writing in MOOCs. Stephen Balfour is an instructional associate professor of psychology and the Director of Information Technology for the College of Liberal Arts at Texas A&M University.
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paper_title: Artificial life programming in the robust-first attractor

paper_content:

Despite mounting awareness of the liabilities of deterministic CPU and RAM computing, across industry and academia there remains little clear vision of a fundamental, generalpurpose alternative. To obtain indefinitely scalable computer architectures offering improved robustness and security, we have advocated a realignment of the roles of hardware and software based on artificial life principles. In this paper we propose an active media computational abstraction to underlie such a hardware-software renegotiation. The active media framework is much in the spirit of probabilistic cellular automata, but designed for indefinite scalability and serious programmability, rather than simplicity and analytic tractability. We discuss active media programming techniques based on living systems principles, and present anecdotal data from sample programs to introduce a new programming language called ulam, that we are developing as an underlying language for active media.
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paper_title: From Here to Eternity—The Theory and Practice of a Really Long Experiment

paper_content:

In February 1988, Richard Lenski set up 12 replicate populations of a single genotype of Escherichia coli in a simple nutrient medium. He has been following their evolution ever since. Here, Lenski answers provocative questions from Jeremy Fox about his iconic "Long-Term Evolution Experiment" (LTEE). The LTEE is a remarkable case study of the interplay of determinism and chance in evolution—and in the conduct of science.
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paper_title: Robust design : a repertoire of biological, ecological, and engineering case studies

paper_content:

Robust Design brings together 16 chapters by an eminent group of authors in a wide range of fields presenting aspects of robustness in biological, ecological, and computational systems. The volume is the first to address robustness in biological, ecological, and computational systems. It is an outgrowth of a new research program on robustness at the Sante Fe Institute founded by the David and Lucile Packard Foundation. For those interested in complexity or interdisciplinary science, robustness is seen as currently among the most intellectually active and promising research areas with important applications in all fields of science, business, and economics.
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paper_title: COEL: A Web-based Chemistry Simulation Framework

paper_content:

The chemical reaction network (CRN) is a widely used formalism to describe macroscopic behavior of chemical systems. Available tools for CRN modelling and simulation require local access, installation, and often involve local le storage, which is susceptible to loss, lacks searchable structure, and does not support concurrency. Furthermore, simulations are often single-threaded, and user interfaces are non-trivial to use. Therefore there are signicant hurdles to conducting ecient and collaborative chemical research. In this paper, we introduce a new enterprise chemistry simulation framework, COEL, which addresses these issues. COEL is the rst web-based framework of its kind. A visually pleasing and intuitive user interface, simulations that run on a large computational grid, reliable database storage, and transactional services make COEL ideal for collaborative research and education. COEL’s most prominent features include ODE-based simulations of chemical reaction networks and multicompartment reaction networks, with rich options for user interactions with those networks. COEL provides DNA-strand displacement transformations and visualization (and is to our knowledge the rst CRN framework to do so), GA optimization of rate constants, expression validation, an application-wide plotting engine, and SBML/Octave/Matlab export. We also present an overview of the underlying software and technologies employed and describe the main architectural decisions driving our development. COEL is available at coel-sim.org for selected research teams only. We plan to provide a part of COEL’s functionality to the general public in the near future.
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paper_title: Bespoke Physics for Living Technology

paper_content:

In the physics of the natural world, basic tasks of life, such as homeostasis and reproduction, are extremely complex operations, requiring the coordination of billions of atoms even in simple cases. By contrast, artificial living organisms can be implemented in computers using relatively few bits, and copying a data structure is trivial. Of course, the physical overheads of the computers themselves are huge, but since their programmability allows digital "laws of physics" to be tailored like a custom suit, deploying living technology atop an engineered computational substrate might be as or more effective than building directly on the natural laws of physics, for a substantial range of desirable purposes. This article suggests basic criteria and metrics for bespoke physics computing architectures, describes one such architecture, and offers data and illustrations of custom living technology competing to reproduce while collaborating on an externally useful computation.
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paper_title: Creating Artificial Life for Interactive Art and Entertainment

paper_content:

This article consists of two sections: the first provides a brief overview of artificial-life art and entertainment software, some of the main products and their peculiarities; and the second describes one of the authors' artificial-life software products, called Life Spacies II, which was created between 1997 and 1999. This system consists of a web page that allows users to create artificial-life creatures by simply typing in text characters using a web page “editor.” Written text is used as genetic code to model the creature's body. The body shape subsequently influences the creature's ability to move, which in turn determines the creature's behavior, survival and reproduction within the Life Spacies II environment. In addition, users of the system can feed the creatures with text characters and thus even more actively influence the creatures' survival and reproduction in their environment.
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paper_title: Concepts of cooperation in artificial life

paper_content:

We have built some simple, but useful, cooperative artificial life agents. Based on this experience and by contrasting our work with computer viruses, we argue that artificial life (the simulation of life including evolution) can only remain reliably and indefinitely cooperative if it adheres to explicitly-specified social conventions. Breaking or neglecting these conventions results in systems that are worse than useless; in fact, malicious with respect to human social values. >
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paper_title: The Creatures Global Digital Ecosystem

paper_content:

An artificial life entertainment-software product called Creatures was released in Europe in late 1996 and in the United States and Japan in mid-1997. When installed on a domestic computer (PC or Macintosh), each Creatures CD-ROM creates a virtual world in which autonomous software agents exist. The agents, known as “norns,” interact with the human user, with each other, and with objects in their virtual world. Each norn coordinates perception and action via its own modular recurrent neural network: Each network has Hebbian learning, plus diffuse modulation of activity via a “hormonal” system that is part of that norn's “biochemistry.” Details of each norn's neural network and biochemistry are genetically specified, and norns can breed via sexual reproduction. In the reproduction process, genetic material may be mutated and may also be subjected to “gene duplications” that enable potentially unlimited increases in complexity of the norns' design. Over 500,000 Creatures CD-ROMS have now been sold. As each ...
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paper_title: Crucial factors in the origins of word-meaning

paper_content:

This work was carried out at the Sony Computer Science Laboratory in Paris and the VUB AI laboratory in Brussels (financed by a GOA grant).
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paper_title: Sodarace: Adventures in Artificial Life

paper_content:

Much like life, the Sodarace project (www.sodarace.net) defies easy description [1]. Originally developed as an online Olympics pitching human against machine intelligence, the project has flourished to incorporate an impressive range of scienceand arts-based activities. Sodarace uses creative play as a bridge to foster dialogue and shared awareness between two very different audiences: a broad public of learners, both in and out of school, and the artificial intelligence and artificial life research communities. The Sodarace project is an extension of the Sodaconstructor software, an online construction kit comprising masses, springs, and muscles, providing tools for open-ended discovery and exploration. Though the mechanics are simple, the forms created often have a very life-like appearance and gait, and as such are frequently anthropomorphized by users.
---
paper_title: Out of Control: The New Biology of Machines, Social Systems, and the Economic World

paper_content:

A review of Out of Control: The New Biology of Machines, Social Systems, and the Economic World, by Kevin Kelly, 1994. Cambridge, MA: Perseus Books, 521pp. ISBN 0201577933. $22.95 USD.
---
paper_title: Sublime Ecologies and Artistic Endeavors: Artificial Life and Interactivity in the Online Project TechnoSphere

paper_content:

THE AUTHOR CHRONICLES HER COLLABORATIVE ONLINE PROJECT TechnoSphere , an interactive artwork accessed via the Internet, exploring some of the issues associated with the work. These include a discussion of the process of collaboration between artists, software engineers, animators, and visitors to the Web site, the thinking behind TechnoSphere’s computer-simulated landscapes, and the focus on interaction with, and within, the project.
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paper_title: Cyberbiogenesis and the EvoGrid: A Twenty-First Century Grand Challenge

paper_content:

The quest for the understanding of the mechanisms of the origin of life on Earth (and by implication elsewhere) could be greatly aided through a synthesis of computer simulation operating at the molecular level and the chemical replication of resultant models in the laboratory. The authors term this synthesis a cyberbiogenesis. The central technological challenge to computing such an “artificial origin of life” is to design computer models permitting de novo emergence of lifelike virtual structures and processes through multiple levels of complexity. This chapter explores cyberbiogenesis by investigating its antecedents, engages in a thought experiment rendered in computer graphics, examines results from an early implementation called the EvoGrid, and concludes by looking at the scientific, technical, religious, and philosophical conundrums presented by such an endeavor.
---
paper_title: Intelligent Information Agents: Agent-Based Information Discovery and Management on the Internet

paper_content:

From the Publisher: ::: This book is the first systematic state-of-the-art survey of intelligent information agents. Eighteen chapters that provide comprehensive coverage of the relevant issues are organized into four parts: cooperative information systems and agents, rational information agents and electronic commerce, adaptive information agents, and mobile information agents and security. Leading authorities and experts in the field offer chapters coherently and concisely written. In addition, the volume editor has provided an introductory survey chapter, highly motivating introductions to each of the four parts, and a comprehensive bibliography with more than 700 entries.
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paper_title: Real artificial life: Where we may be

paper_content:

Artificial life research typically employs digital computers to implement models of living systems. However, there is now a growing if pro-theoretical feeling that computers, or perhaps the software running on them, are themselves some kind of living systems. Such a possibility can impact artificial life research in at least two ways By highlighting that computers and comnnunications networks can be subjects, as well as tools, for artificial life muodelling, and by highlighting that insights, tools, and models from the life sciences can have explanatory, predictive, and design consequences for the construction of future computation and communications systems. This paper seeks perspective on such ‘real artificial life’, looking backwards and forwards at the rise of living systems in manufactured computer and communications systems
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paper_title: Service oriented evolutionary algorithms

paper_content:

This work presents a service oriented architecture for evolutionary algorithms, and an implementation of this architecture using a specific technology (called OSGiLiath). Service oriented architecture is a computational paradigm where users interact using services to increase the integration between systems. The presented abstract architecture is formed by loosely coupled, highly configurable and language-independent services. As an example of an implementation of this architecture, a complete process development using a specific service oriented technology is explained. With this implementation, less effort than classical development in integration, distribution mechanisms and execution time management has been attained. In addition, steps, ideas, advantages and disadvantages, and guidelines to create service oriented evolutionary algorithms are presented. Using existing software, or from scratch, researchers can create services to increase the interoperability in this area.
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paper_title: Collective Intelligence of the Artificial Life Community on Its Own Successes, Failures, and Future

paper_content:

We describe a novel Internet-based method for building consensus and clarifying conflicts in large stakeholder groups facing complex issues, and we use the method to survey and map the scientific and organizational perspectives of the artificial life community during the Seventh International Conference on Artificial Life (summer 2000). The issues addressed in this survey included artificial life's main successes, main failures, main open scientific questions, and main strategies for the future, as well as the benefits and pitfalls of creating a professional society for artificial life. By illuminating the artificial life community's collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups.
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paper_title: Indirectly Encoded Sodarace for Artificial Life

paper_content:

The aim of this paper is to introduce a lightweight twodimensional domain for evolving diverse and interesting artificial creatures. The hope is that this domain will fill a need for such an easily-accessible option for researchers who wish to focus more on the evolutionary dynamics of artificial life scenarios than on building simulators and creature encodings. The proposed domain is inspired by Sodarace, a construction set for two-dimensional creatures made of masses and springs. However, unlike the original Sodarace, the indirectly encoded Sodarace (IESoR) system introduced in this paper allows evolution to discover a wide range of complex and regular ambulating creature morphologies by encoding them with compositional pattern producing networks (CPPNs), which are an established indirect encoding originally introduced for encoding large-scale neural networks. The result, demonstrated through a technique called novelty search with local competition (which are combined through multiobjective search), is that IESoR can discover a wide breadth of interesting and functional creatures, suggesting its potential utility for future experiments in artificial life.
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paper_title: EvoSpace: a distributed evolutionary platform based on the tuple space model

paper_content:

This paper presents EvoSpace, a Cloud service for the development of distributed evolutionary algorithms. EvoSpace is based on the tuple space model, an associatively addressed memory space shared by several processes. Remote clients, called EvoWorkers, connect to EvoSpace and periodically take a subset of individuals from the global population, perform evolutionary operations on them, and return a set of new individuals. Several EvoWorkers carry out the evolutionary search in parallel and asynchronously, interacting with each other through the central repository. EvoSpace is designed to be domain independent and flexible, in the sense that in can be used with different types of evolutionary algorithms and applications. In this paper, a genetic algorithm is tested on the EvoSpace platform using a well-known benchmark problem, achieving promising results compared to a standard evolutionary system.
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paper_title: Evolving content in the Galactic Arms Race video game

paper_content:

Video game content includes the levels, models, items, weapons, and other objects encountered and wielded by players during the game. In most modern video games, the set of content shipped with the game is static and unchanging, or at best, randomized within a narrow set of parameters. However, ideally, if game content could be constantly renewed, players would remain engaged longer in the evolving stream of novel content. To realize this ambition, this paper introduces the content-generating NeuroEvolution of Augmenting Topolo- gies (cgNEAT) algorithm, which automatically evolves game content based on player preferences, as the game is played. To demonstrate this approach, the Galactic Arms Race (GAR) video game is also introduced. In GAR, players pilot space ships and fight enemies to acquire unique particle system weapons that are evolved by the game. As shown in this paper, players can discover a wide variety of content that is not only novel, but also based on and extended from previous content that they preferred in the past. The implication is that it is now possible to create games that generate their own content to satisfy players, potentially significantly reducing the cost of content creation and increasing the replay value of games.
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paper_title: The ALife Zoo: cross-browser, platform-agnostic hosting of Artificial Life simulations

paper_content:

We describe a new approach to sharing software simulations that is of great potential benefit to Artificial Life researchers. youShare is an online collaborative facility that allows users to upload data, and software in the form of services. An attached execution environment allows services to be run over a heterogeneous cluster of compute nodes, where the service infrastructure guarantees that the service will be executed in the correct environment, and provide consistent results. It allows software to be made available as a service regardless of the operating system they run upon. This allows software to be maintained more easily, and to be available to all researchers with internet access. We demonstrate this by making three Artificial Life simulations available over the web: Tierra, Avida and Stringmol. These services form the foundation of an ALife “Zoo”, in which visitors can interact with ALife simulations for research and education. In addition, youShare offers a workflow facility whereby multiple services can be connected to create more complex tasks. We demonstrate the utility of this system in Artificial Life research via a workflow which calculates evolutionary activity for runs of Tierra and Stringmol.
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paper_title: Swarm Chemistry

paper_content:

We propose swarm chemistry a new artificial chemistry framework that uses artificial swarm populations as chemical reactants. Reaction in swarm chemistry is not determined by predefined reaction rules as commonly assumed in typical artificial chemistry studies, but is spontaneously achieved by the emergence of a new spatiotemporal pattern of collective behavior through the kinetic interaction between multiple chemical species. We developed a prototype of an interactive simulation tool with which one can explore the dynamics of swarm chemistry using an interactive evolutionary method. Several preliminary results are reported to illustrate the characteristics and effectiveness of this framework, including spontaneous segregation of distinct chemical species, production and restriction of movements, and interactive design of complex biological-looking structures.
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paper_title: EvoCommander: A Novel Game Based on Evolving and Switching Between Artificial Brains

paper_content:

Neuroevolution [i.e., evolving artificial neural networks (ANNs) through evolutionary algorithms] has shown promise in evolving agents and robot controllers, which display complex behaviors and can adapt to their environments. These properties are also relevant to video games, since they can increase their longevity and replayability. However, the design of most current games precludes the use of any techniques which might yield unpredictable or even open-ended results. This paper describes the game EvoCommander, with the goal to further demonstrate the potential of neuroevolution in games. In EvoCommander the player incrementally evolves an arsenal of ANN-controlled behaviors (e.g., ranged attack, flee, etc.) for a simple robot that has to battle other player and computer controlled robots. The game introduces the novel game mechanic of “brain switching,” selecting which evolved neural network is active at any point during battle. Results from playtests indicate that brain switching is a promising new game mechanic, leading to players employing interesting different strategies when training their robots and when controlling them in battle.
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paper_title: A Stress-based Speciation Model in LifeDrop

paper_content:

This paper presents a stress-based speciation model implemented within LifeDrop, a virtual world with bioinspired agents. In this model, individuals are distributed among species separated by a "barrier" mechanism preventing the reproduction between individuals of different species. An analysis of species dynamics in relation to stress is presented. Results show diversity maintenance and a reactive capacity during crisis situations favoring the emergence of new species.
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paper_title: Picbreeder: A Case Study in Collaborative Evolutionary Exploration of Design Space

paper_content:

For domains in which fitness is subjective or difficult to express formally, interactive evolutionary computation (IEC) is a natural choice. It is possible that a collaborative process combining feedback from multiple users can improve the quality and quantity of generated artifacts. Picbreeder, a large-scale online experiment in collaborative interactive evolution (CIE), explores this potential. Picbreeder is an online community in which users can evolve and share images, and most importantly, continue evolving others' images. Through this process of branching from other images, and through continually increasing image complexity made possible by the underlying neuroevolution of augmenting topologies (NEAT) algorithm, evolved images proliferate unlike in any other current IEC system. This paper discusses not only the strengths of the Picbreeder approach, but its challenges and shortcomings as well, in the hope that lessons learned will inform the design of future CIE systems.
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paper_title: Evolving Neural Networks through Augmenting Topologies

paper_content:

An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. We present a method, NeuroEvolution of Augmenting Topologies (NEAT), which outperforms the best fixed-topology method on a challenging benchmark reinforcement learning task. We claim that the increased efficiency is due to (1) employing a principled method of crossover of different topologies, (2) protecting structural innovation using speciation, and (3) incrementally growing from minimal structure. We test this claim through a series of ablation studies that demonstrate that each component is necessary to the system as a whole and to each other. What results is significantly faster learning. NEAT is also an important contribution to GAs because it shows how it is possible for evolution to both optimize and complexify solutions simultaneously, offering the possibility of evolving increasingly complex solutions over generations, and strengthening the analogy with biological evolution.
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paper_title: Interactive Evolution of Particle Systems for Computer Graphics and Animation

paper_content:

Interactive Evolutionary Computation (IEC) creates the intriguing possibility that a large variety of useful content can be produced quickly and easily for practical computer graphics and gaming applications. To show that IEC can produce such content, this paper applies IEC to particle system effects, which are the de facto method in computer graphics for generating fire, smoke, explosions, electricity, water, and many other special effects. While particle systems are capable of producing a broad array of effects, they require substantial mathematical and programming knowledge to produce. Therefore, efficient particle system generation tools are required for content developers to produce special effects in a timely manner. This paper details the design, representation, and animation of particle systems via two IEC tools called NEAT Particles and NEAT Projectiles. Both tools evolve artificial neural networks (ANN) with the NeuroEvolution of Augmenting Topologies (NEAT) method to control the behavior of particles. NEAT Particles evolves general-purpose particle effects, whereas NEAT Projectiles specializes in evolving particle weapon effects for video games. The primary advantage of this NEAT-based IEC approach is to decouple the creation of new effects from mathematics and programming, enabling content developers without programming knowledge to produce complex effects. Furthermore, it allows content designers to produce a broader range of effects than typical development tools. Finally, it acts as a concept generator, allowing content creators to interactively and efficiently explore the space of possible effects. Both NEAT Particles and NEAT Projectiles demonstrate how IEC can evolve useful content for graphical media and games, and are together a step toward the larger goal of automated content generation.
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paper_title: Automatic design and manufacture of robotic lifeforms

paper_content:

Biological life is in control of its own means of reproduction, which generally involves complex, autocatalysing chemical reactions. But this autonomy of design and manufacture has not yet been realized artificially1. Robots are still laboriously designed and constructed by teams of human engineers, usually at considerable expense. Few robots are available because these costs must be absorbed through mass production, which is justified only for toys, weapons and industrial systems such as automatic teller machines. Here we report the results of a combined computational and experimental approach in which simple electromechanical systems are evolved through simulations from basic building blocks (bars, actuators and artificial neurons); the ‘fittest’ machines (defined by their locomotive ability) are then fabricated robotically using rapid manufacturing technology. We thus achieve autonomy of design and construction using evolution in a ‘limited universe’ physical simulation2,3 coupled to automatic fabrication.
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paper_title: Diversity from a Monoculture - Effects of Mutation-on-Copy in a String-Based Artificial Chemistry

paper_content:

We have developed an artificial chemistry that allows selfmaintaining molecular systems to mutate and exhibit innovative behaviour. The molecular species in the chemistry are defined by strings of symbols that specify both the binding affinity and the reaction. We define a replicase molecule that can copy any other molecule that binds at a particular region on the replicase. Molecules are copied on a symbolby-symbol basis. Occasional mis-copying of an individual symbol forms our mutation scheme. This paper describes the characteristics of the resulting evolutionary system. We ran 1,000 open-ended trials and observed an unexpectedly wide range of emergent phenomena, with many parallels to biological systems. We report these phenomena in qualitative terms, and give details of one of the most interesting among them: the emergence of co-dependent replicase hypercycles.
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paper_title: Picbreeder: evolving pictures collaboratively online

paper_content:

Picbreeder is an online service that allows users to collaboratively evolve images. Like in other Interactive Evolutionary Computation (IEC) programs, users evolve images on Picbreeder by selecting ones that appeal to them to produce a new generation. However, Picbreeder also offers an online community in which to share these images, and most importantly, the ability to continue evolving others' images. Through this process of branching from other images, and through continually increasing image complexity made possible by the NeuroEvolution of Augmenting Topologies (NEAT) algorithm, evolved images proliferate unlike in any other current IEC systems. Participation requires no explicit talent from the users, thereby opening Picbreeder to the entire Internet community. This paper details how Picbreeder encourages innovation, featuring images that were collaboratively evolved.
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paper_title: The Organic Builder: A Public Experiment in Artificial Chemistries and Self-Replication

paper_content:

We describe some results submitted by users of the Organic Builder, a Java applet where the rules of an artificial chemistry can be chosen in order to achieve a desired behavior. Though it was initially intended as a set of challenges to be tackled as a game, the users experimented with the system far beyond this and discovered several novel forms of self-replicators. When searching for a system with certain properties such as self-replication, making the system accessible to the public through a Web site is an unusual but effective way of making scientific discoveries, credit for which must go to the users themselves for their tireless experimentation and innovation.
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paper_title: Interactively Evolving Compositional Sound Synthesis Networks

paper_content:

While the success of electronic music often relies on the uniqueness and quality of selected timbres, many musicians struggle with complicated and expensive equipment and techniques to create their desired sounds. Instead, this paper presents a technique for producing novel timbres that are evolved by the musician through interactive evolutionary computation. Each timbre is produced by an oscillator, which is represented by a special type of artificial neural network (ANN) called a compositional pattern producing network (CPPN). While traditional ANNs compute only sigmoid functions at their hidden nodes, CPPNs can theoretically compute any function and can build on those present in traditional synthesizers (e.g. square, sawtooth, triangle, and sine waves functions) to produce completely novel timbres. Evolved with NeuroEvolution of Augmenting Topologies (NEAT), the aim of this paper is to explore the space of potential sounds that can be generated through such compositional sound synthesis networks (CSSNs). To study the effect of evolution on subjective appreciation, participants in a listener study ranked evolved timbres by personal preference, resulting in preferences skewed toward the first and last generations. In the long run, the CSSN's ability to generate a variety of different and rich timbre opens up the intriguing possibility of evolving a complete CSSN-encoded synthesizer.
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paper_title: Crystal structure of a monomeric retroviral protease solved by protein folding game players

paper_content:

Following the failure of a wide range of attempts to solve the crystal structure of M-PMV retroviral protease by molecular replacement, we challenged players of the protein folding game Foldit to produce accurate models of the protein. Remarkably, Foldit players were able to generate models of sufficient quality for successful molecular replacement and subsequent structure determination. The refined structure provides new insights for the design of antiretroviral drugs.
---
paper_title: Out of Control: The New Biology of Machines, Social Systems, and the Economic World

paper_content:

A review of Out of Control: The New Biology of Machines, Social Systems, and the Economic World, by Kevin Kelly, 1994. Cambridge, MA: Perseus Books, 521pp. ISBN 0201577933. $22.95 USD.
---
paper_title: Intelligent Information Agents: Agent-Based Information Discovery and Management on the Internet

paper_content:

From the Publisher: ::: This book is the first systematic state-of-the-art survey of intelligent information agents. Eighteen chapters that provide comprehensive coverage of the relevant issues are organized into four parts: cooperative information systems and agents, rational information agents and electronic commerce, adaptive information agents, and mobile information agents and security. Leading authorities and experts in the field offer chapters coherently and concisely written. In addition, the volume editor has provided an introductory survey chapter, highly motivating introductions to each of the four parts, and a comprehensive bibliography with more than 700 entries.
---
paper_title: Designing robust volunteer-based evolutionary algorithms

paper_content:

This paper tackles the design of scalable and fault-tolerant evolutionary algorithms computed on volunteer platforms. These platforms aggregate computational resources from contributors all around the world. Given that resources may join the system only for a limited period of time, the challenge of a volunteer-based evolutionary algorithm is to take advantage of a large amount of computational power that in turn is volatile. The paper analyzes first the speed of convergence of massively parallel evolutionary algorithms. Then, it provides some guidance about how to design efficient policies to overcome the algorithmic loss of quality when the system undergoes high rates of transient failures, i.e. computers fail only for a limited period of time and then become available again. In order to provide empirical evidence, experiments were conducted for two well-known problems which require large population sizes to be solved, the first based on a genetic algorithm and the second on genetic programming. Results show that, in general, evolutionary algorithms undergo a graceful degradation under the stress of losing computing nodes. Additionally, new available nodes can also contribute to improving the search process. Despite losing up to 90 % of the initial computing resources, volunteer-based evolutionary algorithms can find the same solutions in a failure-prone as in a failure-free run.
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paper_title: App Epidemics: Modelling the Effects of Publicity in a Mobile App Ecosystem

paper_content:

In mobile app ecosystems, an app can behave like a virus. Once downloaded, it may cause its user to recommend that app to friends who then may download the app and “infect” other friends. Epidemics occur when a small number of downloads causes a snowballing effect that results in a massive number of downloads (and consequently, a rich developer). This paper presents AppEco, the first Artificial Life model of mobile application ecosystems. AppEco models the app store, app developers, apps, users, and their behaviour. We use AppEco to simulate Apple’s iOS app ecosystem and investigate common publicity strategies adopted by developers and their effects on app downloads. Specifically, we investigate three causal factors for a widespread “app infection” from epidemiology: the users’ exposure to the app, the users’ susceptibility to the app, and the infectiousness of the app.
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paper_title: Human based genetic algorithm

paper_content:

A new class of genetic algorithms (GA) is presented. It is based on the idea of outsourcing, a popular trend in business. In a human based genetic algorithm (HBGA), all primary genetic operators are outsourced, i.e. delegated to external human agents. A totally outsourced genetic algorithm uses both human evaluation and the human ability of innovation. It is a multi-agent environment and the mediator of communication between multiple heterogenous agents. The advantage of this approach is its ability to address complex problems for which it is hard, not only to evaluate individuals, but to find a good representation for them. These qualities allow HBGA to process flows of information without knowledge of its particular structure and representation. The suggested conceptual approach can also be used as a general model and a way of thinking about different kinds of genetic algorithms.
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paper_title: Pfeiffer - A Distributed Open-ended Evolutionary System

paper_content:

Pfeiffer contains a population of fractals which has been evolving continuously for more than three years. The animations are developed from embryos using a Lindenmayer grammar (LSystem). These open generative representations potentially allow gene duplication and the evolution of higher order genetic operators and might be a step towards the emergence of social intelligence in swarms of artificial life (alife) agents. The fitness function is simply do the snowflake patterns appeal to the users: interactive evolution (IEC). To this end, images are placed in animated snow globes (computerised snowstorms) by world wide web (www) browsers (Netscape, Mozilla, Internet Explorer, Firefox, etc.) anywhere on the planet. More than 600 people have used http://www.cs.ucl.ac.uk/staff/W.Langdon/pfeiffer.html.
---
paper_title: Interactively Evolving Compositional Sound Synthesis Networks

paper_content:

While the success of electronic music often relies on the uniqueness and quality of selected timbres, many musicians struggle with complicated and expensive equipment and techniques to create their desired sounds. Instead, this paper presents a technique for producing novel timbres that are evolved by the musician through interactive evolutionary computation. Each timbre is produced by an oscillator, which is represented by a special type of artificial neural network (ANN) called a compositional pattern producing network (CPPN). While traditional ANNs compute only sigmoid functions at their hidden nodes, CPPNs can theoretically compute any function and can build on those present in traditional synthesizers (e.g. square, sawtooth, triangle, and sine waves functions) to produce completely novel timbres. Evolved with NeuroEvolution of Augmenting Topologies (NEAT), the aim of this paper is to explore the space of potential sounds that can be generated through such compositional sound synthesis networks (CSSNs). To study the effect of evolution on subjective appreciation, participants in a listener study ranked evolved timbres by personal preference, resulting in preferences skewed toward the first and last generations. In the long run, the CSSN's ability to generate a variety of different and rich timbre opens up the intriguing possibility of evolving a complete CSSN-encoded synthesizer.
---
paper_title: Design Creativity Research: From the Individual to the Crowd

paper_content:

Research in design creativity has focused on individual creativity and on creativity in a collaborative or organizational setting. Collective design and crowdsourcing creativity differ from individual and collaborative creative design by building on the foundations of social computing so that individuals are motivated to contribute voluntarily. Research that improves our understanding and support for these phenomena is a trajectory from existing creativity and design research methods and models that study individuals and teams to studying crowds. Three directions for research in crowdsourcing creativity are: technology development, creative design processes, and evaluating creativity.
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paper_title: How to be a successful app developer: lessons from the simulation of an app ecosystem

paper_content:

App developers are constantly competing against each other to win more downloads for their apps. With hundreds of thousands of apps in these online stores, what strategy should a developer use to be successful? Should they innovate, make many similar apps, optimise their own apps or just copy the apps of others? Looking more deeply, how does a complex app ecosystem perform when developers choose to use different strategies? This paper investigates these questions using AppEco, the first Artificial Life model of mobile application ecosystems. In AppEco, developer agents build and upload apps to the app store; user agents browse the store and download the apps. A distinguishing feature of AppEco is the explicit modelling of apps as artefacts. In this work we use AppEco to simulate Apple's iOS app ecosystem and investigate common developer strategies, evaluating them in terms of downloads received, app diversity, and adoption rate.
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paper_title: A Stress-based Speciation Model in LifeDrop

paper_content:

This paper presents a stress-based speciation model implemented within LifeDrop, a virtual world with bioinspired agents. In this model, individuals are distributed among species separated by a "barrier" mechanism preventing the reproduction between individuals of different species. An analysis of species dynamics in relation to stress is presented. Results show diversity maintenance and a reactive capacity during crisis situations favoring the emergence of new species.
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paper_title: The coreworld: emergence and evolution of cooperative structures in a computational chemistry

paper_content:

Abstract We have developed an artificial chemistry in the computer core, where one is able to evolve assembler-automaton code without any predefined evolutionary path. The core simulator in the present version has one dimension, is updated in parallel, the instructions are only able to communicate locally, and the system is continuously subjected to noise. The system also has a notion of local computational resources. We see different evolutionary paths depending on the specified parameters and the level of complexity, measured as distance from initially randomized core. For several initial conditions the system is able to develop extremely viable cooperative structures (organisms?) which totally dominate the core. We have been able to identify seven successive evolutionary epochs each characterized by different functional properties. Our study demonstrates a successive emergence of complex functional properties in a computational environment.
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paper_title: Creating Artificial Life for Interactive Art and Entertainment

paper_content:

This article consists of two sections: the first provides a brief overview of artificial-life art and entertainment software, some of the main products and their peculiarities; and the second describes one of the authors' artificial-life software products, called Life Spacies II, which was created between 1997 and 1999. This system consists of a web page that allows users to create artificial-life creatures by simply typing in text characters using a web page “editor.” Written text is used as genetic code to model the creature's body. The body shape subsequently influences the creature's ability to move, which in turn determines the creature's behavior, survival and reproduction within the Life Spacies II environment. In addition, users of the system can feed the creatures with text characters and thus even more actively influence the creatures' survival and reproduction in their environment.
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paper_title: Modeling browser-based distributed evolutionary computation systems

paper_content:

From the era of big science we are back to the "do it yourself", where you do not have any money to buy clusters or subscribe to grids but still have algorithms that crave many computing nodes and need them to measure scalability. Fortunately, this coincides with the era of big data, cloud computing, and browsers that include JavaScript virtual machines. Those are the reasons why this paper will focus on two different aspects of volunteer or freeriding computing: first, the pragmatic: where to find those resources, which ones can be used, what kind of support you have to give them; and then, the theoretical: how evolutionary algorithms can be adapted to an environment in which nodes come and go, have different computing capabilities and operate in complete asynchrony of each other. We will examine the setup needed to create a very simple distributed evolutionary algorithm using JavaScript and then find a model of how users react to it by collecting data from several experiments featuring different classical benchmark functions.
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paper_title: Pfeiffer - A Distributed Open-ended Evolutionary System

paper_content:

Pfeiffer contains a population of fractals which has been evolving continuously for more than three years. The animations are developed from embryos using a Lindenmayer grammar (LSystem). These open generative representations potentially allow gene duplication and the evolution of higher order genetic operators and might be a step towards the emergence of social intelligence in swarms of artificial life (alife) agents. The fitness function is simply do the snowflake patterns appeal to the users: interactive evolution (IEC). To this end, images are placed in animated snow globes (computerised snowstorms) by world wide web (www) browsers (Netscape, Mozilla, Internet Explorer, Firefox, etc.) anywhere on the planet. More than 600 people have used http://www.cs.ucl.ac.uk/staff/W.Langdon/pfeiffer.html.
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paper_title: Cloud-based evolutionary algorithms: An algorithmic study

paper_content:

This paper presents a cloud-computing based evolutionary algorithm using a synchronous storage service as pool for exchange information among population of solutions. The multi-computer was composed of several normal PCs or laptops connected via Wifi or Ethernet. In this work the effect of how the distributed evolutionary algorithm reached the solution when new PCs was added was tested whether that effect also translates to the algorithmic performance of the algorithm. To this end different (and hard) problems was addressed using the proposed multi-computer, analyzing the effects that the automatic load-balancing and synchronization had on the speed of algorithm successful, and analyzing how the number of evaluation per second increases when the multi-computer includes new nodes. The measure used for the analysis was number of evaluation per second which was increased when the multi-computer includes new nodes. The algorithm solved the proposed problems and it was viable to run it in homogeneous or heterogeneous platforms. The experiments includes two problems and different configuration for the distributed evolutionary algorithm in order to check the results of the algorithm for several rates of information exchange with the selected storage service. Results shows that the system is viable with homogeneous or heterogeneous nodes and there is no significative differences for the synchronous storage services we have tested. But when the problem is harder, and the threads of the algorithm does not stop for each information exchange (migration of individual from one population to another one), the differences of using a specific service became significative in terms of success of the algorithm.
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paper_title: Automatic design and manufacture of robotic lifeforms

paper_content:

Biological life is in control of its own means of reproduction, which generally involves complex, autocatalysing chemical reactions. But this autonomy of design and manufacture has not yet been realized artificially1. Robots are still laboriously designed and constructed by teams of human engineers, usually at considerable expense. Few robots are available because these costs must be absorbed through mass production, which is justified only for toys, weapons and industrial systems such as automatic teller machines. Here we report the results of a combined computational and experimental approach in which simple electromechanical systems are evolved through simulations from basic building blocks (bars, actuators and artificial neurons); the ‘fittest’ machines (defined by their locomotive ability) are then fabricated robotically using rapid manufacturing technology. We thus achieve autonomy of design and construction using evolution in a ‘limited universe’ physical simulation2,3 coupled to automatic fabrication.
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paper_title: Harnessing Crowds: Mapping the Genome of Collective Intelligence

paper_content:

Over the past decade, the rise of the Internet has enabled the emergence of surprising new forms of collective intelligence. Examples include Google, Wikipedia, Threadless, and many others. To take advantage of the possibilities these new systems represent, it is necessary to go beyond just seeing them as a fuzzy collection of "cool" ideas. What is needed is a deeper understanding of how these systems work. This article offers a new framework to help provide that understanding. It identifies the underlying building blocks - to use a biological metaphor, the "genes" - at the heart of collective intelligence systems. These genes are defined by the answers to two pairs of key questions: - Who is performing the task? Why are they doing it? - What is being accomplished? How is it being done? The paper goes on to list the genes of collective intelligence - the possible answers to these key questions - and shows how combinations of genes comprise a "genome" that characterizes each collective intelligence system. In addition, the paper describes the conditions under which each gene is useful and the possibilities for combining and re-combining these genes to harness crowds effectively. Using this framework, managers can systematically consider many possible combinations of genes as they seek to develop new collective intelligence systems.
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paper_title: Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning

paper_content:

The Achilles Heel of stochastic optimization algorithms is getting trapped on local optima. Novelty Search avoids this problem by encouraging a search in all interesting directions. That occurs by replacing a performance objective with a reward for novel behaviors, as defined by a human-crafted, and often simple, behavioral distance function. While Novelty Search is a major conceptual breakthrough and outperforms traditional stochastic optimization on certain problems, it is not clear how to apply it to challenging, high-dimensional problems where specifying a useful behavioral distance function is difficult. For example, in the space of images, how do you encourage novelty to produce hawks and heroes instead of endless pixel static? Here we propose a new algorithm, the Innovation Engine, that builds on Novelty Search by replacing the human-crafted behavioral distance with a Deep Neural Network (DNN) that can recognize interesting differences between phenotypes. The key insight is that DNNs can recognize similarities and differences between phenotypes at an abstract level, wherein novelty means interesting novelty. For example, a novelty pressure in image space does not explore in the low-level pixel space, but instead creates a pressure to create new types of images (e.g. churches, mosques, obelisks, etc.). Here we describe the long-term vision for the Innovation Engine algorithm, which involves many technical challenges that remain to be solved. We then implement a simplified version of the algorithm that enables us to explore some of the algorithm's key motivations. Our initial results, in the domain of images, suggest that Innovation Engines could ultimately automate the production of endless streams of interesting solutions in any domain: e.g. producing intelligent software, robot controllers, optimized physical components, and art.
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paper_title: The future of citizen science: emerging technologies and shifting paradigms

paper_content:

Citizen science creates a nexus between science and education that, when coupled with emerging technologies, expands the frontiers of ecological research and public engagement. Using representative technologies and other examples, we examine the future of citizen science in terms of its research processes, program and participant cultures, and scientific communities. Future citizen-science projects will likely be influenced by sociocultural issues related to new technologies and will continue to face practical programmatic challenges. We foresee networked, open science and the use of online computer/video gaming as important tools to engage non-traditional audiences, and offer recommendations to help prepare project managers for impending challenges. A more formalized citizen-science enterprise, complete with networked organizations, associations, journals, and cyberinfrastructure, will advance scientific research, including ecology, and further public education.
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paper_title: Evolving three-dimensional objects with a generative encoding inspired by developmental biology

paper_content:

This paper introduces an algorithm for evolving 3D objects with a generative encoding that abstracts how biological morphologies are produced. Evolving interesting 3D objects is useful in many disciplines, including artistic design (e.g. sculpture), engineering (e.g. robotics, architecture, or product design), and biology (e.g. for investigating morphological evolution). A critical element in evolving 3D objects is the representation, which strongly influences the types of objects produced. In 2007 a representation was introduced called Compositional Pattern Producing Networks (CPPN), which abstracts how natural phenotypes are generated. To date, however, the ability of CPPNs to create 3D objects has barely been explored. Here we present a new way to create 3D objects with CPPNs. Experiments with both interactive and target-based evolution demonstrate that CPPNs show potential in generating interesting, complex, 3D objects. We further show that changing the information provided to CPPNs and the functions allowed in their genomes biases the types of objects produced. Finally, we validate that the objects transfer well from simulation to the real-world by printing them with a 3D printer. Overall, this paper shows that evolving objects with encodings based on concepts from biological development can be a powerful way to evolve complex, interesting objects, which should be of use in fields as diverse as art, engineering, and biology. Motivation and Previous Work The diversity, complexity, and function of natural morphologies is awe-inspiring. Evolution has created bodies that can fly, run, and swim with amazing agility. It would be desirable to harness the power of evolution to create synthetic physical designs and morphologies. Doing so would benefit a variety of fields. For example, artists, architects and engineers could evolve sculptures, buildings, product designs, and sophisticated robots. Evolution should be especially helpful in the design of complex objects with many interacting parts made of non-linear materials. In such challenging problem domains, evolution excels while human intuition is limited. Being able to evolve sophisticated morphologies also furthers biological research because it enables the investigation of how and why certain natural designs were produced. Evolving 3D objects is thus worthwhile both as a Figure 1: Examples of evolved objects that were transferred to reality via a 3D printer. basic science and for its innumerable potential applications. This paper describes how 3D shapes can be evolved and then transferred to reality via 3D printing technology (Figure 1). Previous research in digital morphological evolution has typically involved encodings that were either highly biologically detailed, or highly-abstract with less biological accuracy. The former camp frequently simulates the low-level processes that govern biological development, such as the diffusing morphogen chemicals and proteins that determine the identity of embryonic cells (Bongard and Pfeifer 2001, Eggenberger 1997, Miller 2004). While this approach facilitates studying the mechanisms of developmental biology, the computational cost of simulating chemistry in such detail greatly limits the complexity of the evolved phenotypes. The most complex forms typically evolved in such systems are simple geometric patterns (such as three bands) (Miller 2004) or groups of shapes resembling the earliest stages of animal development (Eggenberger 1997). The second camp employs high-level abstractions that enable the evolution of more elaborate forms with many parts, but these abstractions tend not to reflect the way that organisms actually develop (Wolpert and Tickle 2010, Bentley 1996). An example is Lindenmayer Systems (L-Systems), which iteratively replace symbols in strings with other symbols until a termination criteria is reached (Lindenmayer 1968, Hornby et al. 2003). While L-Systems can reproduce a wide variety of organismal shapes, especially those of branching plants, they do not model plant developmental processes (Wolpert and Tickle 2010). Another example is the work of Sims (1994), who evolved morphologies that resembled some biological creatures, although with an abstract encoding based on parameterized recursion that does not resemble natural developmental processes (Sims 1994). A third option is possible, wherein a high-level abstraction is based on the developmental processes that give rise to natural forms. An example of this approach is Compositional Pattern Producing Networks (CPPNs) (Stanley 2007), which are used to evolve 3D objects in this paper and are described in Methods. Two groups have previously evolved 3D objects with CPPNs, although neither conducted an openended exploration of 3D objects. One group evolved CPPN objects that were composed of variable-sized spheres and were evaluated on two tasks: falling (Auerbach and Bongard 2010b) or moving rapidly (Auerbach and Bongard 2010a). Most of the evolved forms resembled clubs. A second group evolved soft-bodied robots to move quickly (Hiller and Lipson 2010). These studies demonstrate that CPPNs can create functional shapes, but leave open the question of what types of 3D objects CPPNs can produce with fewer constraints and without specific objectives. 2D pictures are evolved with CPPNs on picbreeder.org, where humans perform selection (Secretan et al. 2011). The complexity and natural appearance of the resulting images often support claims regarding the legitimacy of CPPNs as an abstraction of biological development (Stanley 2007). A demonstration in 3D would significantly strengthen these claims, however, because the natural world is 3D. It is possible that CPPNs are unable to frequently make sensible forms with the added difficulty of another dimension, and when objects must be one contiguous unit (which aids in transfers to reality). A recent paper by Bansagi Jr et al. (Science 2011) highlights the need to verify that generative encodings that produce complex patterns in 2D also can do so in 3D. By evolving CPPN objects in the natural 3D setting, this paper conducts a critical test of the hypothesis that generative encodings based on geometric abstractions of development capture some of the complexity-generating power of natural morphological development. Doing so also provides a visually intuitive testbed for studying how variants of such generative encodings behave. It also reveals the utility of CPPNs as a representation for 3D object design.
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paper_title: Evolutionary Robotics on the Web with WebGL and Javascript

paper_content:

Web-based applications are highly accessible to users, providing rich, interactive content while eliminating the need to install software locally. However, evolutionary robotics (ER) has faced challenges in this domain as web-based technologies have not been amenable to 3D physics simulations. Traditionally, physics-based simulations require a local installation and a high degree of user knowledge to configure an environment, but the emergence of Javascript-based physics engines enables complex simulations to be executed in web browsers. These developments create opportunities for ER research to reach new audiences by increasing accessibility. In this work, we introduce two web-based tools we have built to facilitate the exchange of ideas with other researchers as well as outreach to K-12 students and the general public. The first tool is intended to distribute and exchange ER research results, while the second is a completely browser-based implementation of an ER environment.
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paper_title: Self-organization on social media: endo-exo bursts and baseline fluctuations

paper_content:

A salient dynamic property of social media is bursting behavior. In this paper, we study bursting behavior in terms of the temporal relation between a preceding baseline fluctuation and the successive burst response using a frequency time series of 3,000 keywords on Twitter. We found that there is a fluctuation threshold up to which the burst size increases as the fluctuation increases and that above the threshold, there appears a variety of burst sizes. We call this threshold the critical threshold. Investigating this threshold in relation to endogenous bursts and exogenous bursts based on peak ratio and burst size reveals that the bursts below this threshold are endogenously caused and above this threshold, exogenous bursts emerge. Analysis of the 3,000 keywords shows that all the nouns have both endogenous and exogenous origins of bursts and that each keyword has a critical threshold in the baseline fluctuation value to distinguish between the two. Having a threshold for an input value for activating the system implies that Twitter is an excitable medium. These findings are useful for characterizing how excitable a keyword is on Twitter and could be used, for example, to predict the response to particular information on social media.
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paper_title: Interactively Evolving Compositional Sound Synthesis Networks

paper_content:

While the success of electronic music often relies on the uniqueness and quality of selected timbres, many musicians struggle with complicated and expensive equipment and techniques to create their desired sounds. Instead, this paper presents a technique for producing novel timbres that are evolved by the musician through interactive evolutionary computation. Each timbre is produced by an oscillator, which is represented by a special type of artificial neural network (ANN) called a compositional pattern producing network (CPPN). While traditional ANNs compute only sigmoid functions at their hidden nodes, CPPNs can theoretically compute any function and can build on those present in traditional synthesizers (e.g. square, sawtooth, triangle, and sine waves functions) to produce completely novel timbres. Evolved with NeuroEvolution of Augmenting Topologies (NEAT), the aim of this paper is to explore the space of potential sounds that can be generated through such compositional sound synthesis networks (CSSNs). To study the effect of evolution on subjective appreciation, participants in a listener study ranked evolved timbres by personal preference, resulting in preferences skewed toward the first and last generations. In the long run, the CSSN's ability to generate a variety of different and rich timbre opens up the intriguing possibility of evolving a complete CSSN-encoded synthesizer.
---
paper_title: Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning

paper_content:

The Achilles Heel of stochastic optimization algorithms is getting trapped on local optima. Novelty Search avoids this problem by encouraging a search in all interesting directions. That occurs by replacing a performance objective with a reward for novel behaviors, as defined by a human-crafted, and often simple, behavioral distance function. While Novelty Search is a major conceptual breakthrough and outperforms traditional stochastic optimization on certain problems, it is not clear how to apply it to challenging, high-dimensional problems where specifying a useful behavioral distance function is difficult. For example, in the space of images, how do you encourage novelty to produce hawks and heroes instead of endless pixel static? Here we propose a new algorithm, the Innovation Engine, that builds on Novelty Search by replacing the human-crafted behavioral distance with a Deep Neural Network (DNN) that can recognize interesting differences between phenotypes. The key insight is that DNNs can recognize similarities and differences between phenotypes at an abstract level, wherein novelty means interesting novelty. For example, a novelty pressure in image space does not explore in the low-level pixel space, but instead creates a pressure to create new types of images (e.g. churches, mosques, obelisks, etc.). Here we describe the long-term vision for the Innovation Engine algorithm, which involves many technical challenges that remain to be solved. We then implement a simplified version of the algorithm that enables us to explore some of the algorithm's key motivations. Our initial results, in the domain of images, suggest that Innovation Engines could ultimately automate the production of endless streams of interesting solutions in any domain: e.g. producing intelligent software, robot controllers, optimized physical components, and art.
---
paper_title: Automated Evolution of Interesting Images

paper_content:

Note: The Humanities and ALife -- Best Presentation Award Winner. Reference EPFL-CONF-191282 Record created on 2013-12-13, modified on 2017-05-10
---
paper_title: DrawCompileEvolve: Sparking Interactive Evolutionary Art with Human Creations

paper_content:

This paper presents DrawCompileEvolve, a web-based drawing tool which allows users to draw simple primitive shapes, group them together or define patterns in their groupings (e.g. symmetry, repetition). The user’s vector drawing is then compiled into an indirectly encoded genetic representation, which can be evolved interactively, allowing the user to change the image’s colors, patterns and ultimately transform it. The human artist has direct control while drawing the initial seed of an evolutionary run and indirect control while interactively evolving it, thus making DrawCompileEvolve a mixed-initiative art tool. Early results in this paper show the potential of DrawCompileEvolve to jump-start evolutionary art with meaningful drawings as well as the power of the underlying genetic representation to transform the user’s initial drawing into a different, yet potentially meaningful, artistic rendering.
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paper_title: ImageNet: A large-scale hierarchical image database

paper_content:

The explosion of image data on the Internet has the potential to foster more sophisticated and robust models and algorithms to index, retrieve, organize and interact with images and multimedia data. But exactly how such data can be harnessed and organized remains a critical problem. We introduce here a new database called “ImageNet”, a large-scale ontology of images built upon the backbone of the WordNet structure. ImageNet aims to populate the majority of the 80,000 synsets of WordNet with an average of 500-1000 clean and full resolution images. This will result in tens of millions of annotated images organized by the semantic hierarchy of WordNet. This paper offers a detailed analysis of ImageNet in its current state: 12 subtrees with 5247 synsets and 3.2 million images in total. We show that ImageNet is much larger in scale and diversity and much more accurate than the current image datasets. Constructing such a large-scale database is a challenging task. We describe the data collection scheme with Amazon Mechanical Turk. Lastly, we illustrate the usefulness of ImageNet through three simple applications in object recognition, image classification and automatic object clustering. We hope that the scale, accuracy, diversity and hierarchical structure of ImageNet can offer unparalleled opportunities to researchers in the computer vision community and beyond.
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paper_title: ALife Meets Web: Lessons Learned

paper_content:

Artificial life might come to play important roles for the World Wide Web, both as a source of new algorithmic paradigms and as a source of inspiration for its future development. New Web searching and managing techniques, based on artificial life principles, have been elicited by the striking similarities between the Web and natural environments. New Web interface designs, based on artificial life techniques, have resulted in increased aesthetic appeal, smart animations, and clever interactive rules. In this paper we exemplify these observations by surveying a number of meeting points between artificial life and the Web. We touch on a few implementation issues and attempt to draw some lessons to be learned from these early experiences.
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paper_title: Exploring Default Mode and Information Flow on the Web

paper_content:

Social networking services (e.g., Twitter, Facebook) are now major sources of World Wide Web (called “Web”) dynamics, together with Web search services (e.g., Google). These two types of Web services mutually influence each other but generate different dynamics. In this paper, we distinguish two modes of Web dynamics: the reactive mode and the default mode. It is assumed that Twitter messages (called “tweets”) and Google search queries react to significant social movements and events, but they also demonstrate signs of becoming self-activated, thereby forming a baseline Web activity. We define the former as the reactive mode and the latter as the default mode of the Web. In this paper, we investigate these reactive and default modes of the Web's dynamics using transfer entropy (TE). The amount of information transferred between a time series of 1,000 frequent keywords in Twitter and the same keywords in Google queries is investigated across an 11-month time period. Study of the information flow on Google and Twitter revealed that information is generally transferred from Twitter to Google, indicating that Twitter time series have some preceding information about Google time series. We also studied the information flow among different Twitter keywords time series by taking keywords as nodes and flow directions as edges of a network. An analysis of this network revealed that frequent keywords tend to become an information source and infrequent keywords tend to become sink for other keywords. Based on these findings, we hypothesize that frequent keywords form the Web's default mode, which becomes an information source for infrequent keywords that generally form the Web's reactive mode. We also found that the Web consists of different time resolutions with respect to TE among Twitter keywords, which will be another focal point of this paper.
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paper_title: Dynamic homeostasis in packet switching networks

paper_content:

In this study, we investigate the adaptation and robustness of a packet switching network (PSN), the fundamental architecture of the Internet. We claim that the adaptation introduced by a transmission control protocol congestion control mechanism is interpretable as the self-organization of complex itinerant behavior among many quasi-attracting states. To discuss this argument quantitatively, we study the adaptation of the Internet by simulating a PSN using ns-2. Our hypothesis is that the robustness and fragility of the Internet can be attributed to the inherent dynamics of the PSN feedback mechanism called the congestion window size, or cwnd. By varying the data input into the PSN system, we demonstrate the possible self-organization of attractors in cwnd temporal dynamics and discuss the adaptability and robustness of PSNs. The present study provides an example of Ashby's Law of Requisite Variety in action.
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paper_title: BrainCrafter: An investigation into human-based neural network engineering

paper_content:

This paper presents the online application Brain-Crafter, in which users can manually build artificial neural networks (ANNs) to control a robot in a maze environment. Users can either start to construct networks from scratch or elaborate on networks created by other users. In particular, BrainCrafter was designed to study how good we as humans are at building ANNs for control problems and if collaborating with other users can facilitate this process. The results in this paper show that (1) some users were in fact able to successfully construct ANNs that solve the navigation tasks, (2) collaboration between users presented difficulties and (3) the human-developed ANNs that managed to solve the task had certain regularities, suggesting that humans can use some of their intuition and spatial understanding in the design of ANNs. Most importantly, the initial results in this paper can serve as a starting point for investigating how to best combine human and machine design capabilities to create more complex artificial brains.
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paper_title: Combining search-based procedural content generation and social gaming in the petalz video game

paper_content:

Search-based procedural content generation methods allow video games to introduce new content continually, thereby engaging the player for a longer time while reducing the burden on developers. However, games so far have not explored the potential economic value of unique evolved artifacts. Building on this insight, this paper presents for the first time a Facebook game called Petalz in which players can share flowers they breed themselves with other players through a global marketplace. In particular, the market in this social game allows players to set the price of their evolved aesthetically-pleasing flowers in virtual currency. Furthermore, the transaction in which one player buys seeds from another creates a new social element that links the players in the transaction. The combination of unique user-generated content and social gaming in Petalz facilitates meaningful collaboration between users, positively influences the dynamics of the game, and opens new possibilities in digital entertainment.
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paper_title: Automated Evolution of Interesting Images

paper_content:

Note: The Humanities and ALife -- Best Presentation Award Winner. Reference EPFL-CONF-191282 Record created on 2013-12-13, modified on 2017-05-10
---
paper_title: Towards a virtual C. elegans: a framework for simulation and visualization of the neuromuscular system in a 3D physical environment.

paper_content:

The nematode C. elegans is the only animal with a known neuronal wiring diagram, or "connectome". During the last three decades, extensive studies of the C. elegans have provided wide-ranging data about it, but few systematic ways of inte- grating these data into a dynamic model have been put forward. Here we present a detailed demonstration of a virtual C. elegans aimed at integrating these data in the form of a 3D dynamic model operating in a simulated physical environment. Our current demonstration includes a realistic flexible worm body model, muscular system and a partially implemented ventral neural cord. Our virtual C. elegans demonstrates successful forward and backward locomotion when sending sinusoidal patterns of neuronal activity to groups of motor neurons. To account for the relatively slow propagation velocity and the attenuation of neuronal sig- nals, we introduced "pseudo neurons" into our model to simulate simplified neuronal dynamics. The pseudo neurons also pro- vide a good way of visualizing the nervous system's structure and activity dynamics.
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paper_title: The Case for a Mixed-Initiative Collaborative Neuroevolution Approach

paper_content:

It is clear that the current attempts at using algorithms to create artificial neural networks have had mixed success at best when it comes to creating large networks and/or complex behavior. This should not be unexpected, as creating an artificial brain is essentially a design problem. Human design ingenuity still surpasses computational design for most tasks in most domains, including architecture, game design, and authoring literary fiction. This leads us to ask which the best way is to combine human and machine design capacities when it comes to designing artificial brains. Both of them have their strengths and weaknesses; for example, humans are much too slow to manually specify thousands of neurons, let alone the billions of neurons that go into a human brain, but on the other hand they can rely on a vast repository of common-sense understanding and design heuristics that can help them perform a much better guided search in design space than an algorithm. Therefore, in this paper we argue for a mixed-initiative approach for collaborative online brain building and present first results towards this goal.
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paper_title: EvoCommander: A Novel Game Based on Evolving and Switching Between Artificial Brains

paper_content:

Neuroevolution [i.e., evolving artificial neural networks (ANNs) through evolutionary algorithms] has shown promise in evolving agents and robot controllers, which display complex behaviors and can adapt to their environments. These properties are also relevant to video games, since they can increase their longevity and replayability. However, the design of most current games precludes the use of any techniques which might yield unpredictable or even open-ended results. This paper describes the game EvoCommander, with the goal to further demonstrate the potential of neuroevolution in games. In EvoCommander the player incrementally evolves an arsenal of ANN-controlled behaviors (e.g., ranged attack, flee, etc.) for a simple robot that has to battle other player and computer controlled robots. The game introduces the novel game mechanic of “brain switching,” selecting which evolved neural network is active at any point during battle. Results from playtests indicate that brain switching is a promising new game mechanic, leading to players employing interesting different strategies when training their robots and when controlling them in battle.
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paper_title: Petalz: Search-Based Procedural Content Generation for the Casual Gamer

paper_content:

The impact of game content on the player experience is potentially more critical in casual games than in competitive games because of the diminished role of strategic or tactical diversions. Interestingly, until now procedural content generation (PCG) has nevertheless been investigated almost exclusively in the context of competitive, skills-based gaming. This paper therefore opens a new direction for PCG by placing it at the center of an entirely casual flower-breeding game platform called Petalz. That way, the behavior of players and their reactions to different game mechanics in a casual environment driven by PCG can be investigated. In particular, players in Petalz can: 1) trade their discoveries in a global marketplace; 2) respond to an incentive system that awards diversity; and 3) generate real-world 3-D replicas of their evolved flowers. With over 1900 registered online users and 38 646 unique evolved flowers, Petalz showcases the potential for PCG to enable these kinds of casual game mechanics, thus paving the way for continued innovation with PCG in casual gaming.
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paper_title: Interactive evolution of levels for a competitive multiplayer FPS

paper_content:

Traditionally a dedicated level designer has to create every aspect of a level by hand, distribute and gather people to test it. Especially for multiplayer maps, the cyclic process of developing and testing can be quite cumbersome and time consuming. This paper presents a novel approach to provide live generation of levels for such multiplayer maps through procedural content generation and interactive evolution. The approach is demonstrated in the FPSEvolver video game that aims at replicating the look and feel of popular games like Counter-Strike. Without leaving the game a group of players can generate, play and improve levels to fit their particular preferences by voting on a selection of evolving levels. This approach focuses on maintaining the level design principles for modern first-person shooters that encourages good engagements between players, in the popular game mode “bomb defusal”. The presented approach can generate enjoyable maps that adapt to the preferences of players across a range of skill levels. Several distinct types of levels were created during testing, which range from open to closed, and complex to simple, each fitting closely with what the different players consider a good map.
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paper_title: Learning Evolution and the Nature of Science LEARNING EVOLUTION AND THE NATURE OF SCIENCE USING EVOLUTIONARY COMPUTING AND ARTIFICIAL LIFE

paper_content:

Because evolution in natural systems happens so slowly, it is dif- ficult to design inquiry-based labs where students can experiment and observe evolution in the way they can when studying other phenomena. New research in evolutionary computation and artificial life provides a solution to this problem. This paper describes a new A-Life software environment - Avida-ED - in which undergraduate students can test evolutionary hypotheses directly using digital organisms that evolve on their own through the very mechanisms that Darwin discovered. APPRENDRE L'EVOLUTION ET LA NATURE DES SCIENCES AU MOYEN DU CALCUL
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paper_title: How to be a successful app developer: lessons from the simulation of an app ecosystem

paper_content:

App developers are constantly competing against each other to win more downloads for their apps. With hundreds of thousands of apps in these online stores, what strategy should a developer use to be successful? Should they innovate, make many similar apps, optimise their own apps or just copy the apps of others? Looking more deeply, how does a complex app ecosystem perform when developers choose to use different strategies? This paper investigates these questions using AppEco, the first Artificial Life model of mobile application ecosystems. In AppEco, developer agents build and upload apps to the app store; user agents browse the store and download the apps. A distinguishing feature of AppEco is the explicit modelling of apps as artefacts. In this work we use AppEco to simulate Apple's iOS app ecosystem and investigate common developer strategies, evaluating them in terms of downloads received, app diversity, and adoption rate.
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paper_title: Collective Intelligence of the Artificial Life Community on Its Own Successes, Failures, and Future

paper_content:

We describe a novel Internet-based method for building consensus and clarifying conflicts in large stakeholder groups facing complex issues, and we use the method to survey and map the scientific and organizational perspectives of the artificial life community during the Seventh International Conference on Artificial Life (summer 2000). The issues addressed in this survey included artificial life's main successes, main failures, main open scientific questions, and main strategies for the future, as well as the benefits and pitfalls of creating a professional society for artificial life. By illuminating the artificial life community's collective perspective on these issues, this survey illustrates the value of such methods of harnessing the collective intelligence of large stakeholder groups.
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paper_title: Investigating app store ranking algorithms using a simulation of mobile app ecosystems

paper_content:

App stores are one of the most popular ways of providing content to mobile device users today. But with thousands of competing apps and thousands new each day, the problem of presenting the developers' apps to users becomes nontrivial. There may be an app for everything, but if the user cannot find the app they desire, then the app store has failed. This paper investigates app store content organisation using AppEco, an Artificial Life model of mobile app ecosystems. In AppEco, developer agents build and upload apps to the app store; user agents browse the store and download the apps. This paper uses AppEco to investigate how best to organise the Top Apps Chart and New Apps Chart in Apple's iOS App Store. We study the effects of different app ranking algorithms for the Top Apps Chart and the frequency of updates of the New Apps Chart on the download-to-browse ratio. Results show that the effectiveness of the shop front is highly dependent on the speed at which content is updated. A slowly updated New Apps Chart will impact the effectiveness of the Top Apps Chart. A Top Apps Chart that measures success by including too much historical data will also detrimentally affect app downloads.
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paper_title: App Epidemics: Modelling the Effects of Publicity in a Mobile App Ecosystem

paper_content:

In mobile app ecosystems, an app can behave like a virus. Once downloaded, it may cause its user to recommend that app to friends who then may download the app and “infect” other friends. Epidemics occur when a small number of downloads causes a snowballing effect that results in a massive number of downloads (and consequently, a rich developer). This paper presents AppEco, the first Artificial Life model of mobile application ecosystems. AppEco models the app store, app developers, apps, users, and their behaviour. We use AppEco to simulate Apple’s iOS app ecosystem and investigate common publicity strategies adopted by developers and their effects on app downloads. Specifically, we investigate three causal factors for a widespread “app infection” from epidemiology: the users’ exposure to the app, the users’ susceptibility to the app, and the infectiousness of the app.
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paper_title: Using MapReduce Streaming for Distributed Life Simulation on the Cloud

paper_content:

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models 1 .
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paper_title: Human computation: a survey and taxonomy of a growing field

paper_content:

The rapid growth of human computation within research and industry has produced many novel ideas aimed at organizing web users to do great things. However, the growth is not adequately supported by a framework with which to understand each new system in the context of the old. We classify human computation systems to help identify parallels between different systems and reveal "holes" in the existing work as opportunities for new research. Since human computation is often confused with "crowdsourcing" and other terms, we explore the position of human computation with respect to these related topics.
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paper_title: Crowdseeding: A Novel Approach for Designing Bioinspired Machines

paper_content:

Crowdsourcing is a popular technique for distributing tasks to a group of anonymous workers over the web. Similarly, crowdseeding is any mechanism that extracts knowledge from the crowd, and then uses that knowledge to guide an automated process. Here we demonstrate a method that automatically distills features from a set of robot body plans designed by the crowd, and then uses those features to guide the automated design of robot body plans and controllers. This approach outperforms past work in which one feature was detected and distilled manually. This provides evidence that the crowd collectively possesses intuitions about the biomechanical advantages of certain body plans; we hypothesize that these intuitions derive from their experiences with biological organisms.
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paper_title: Combining search-based procedural content generation and social gaming in the petalz video game

paper_content:

Search-based procedural content generation methods allow video games to introduce new content continually, thereby engaging the player for a longer time while reducing the burden on developers. However, games so far have not explored the potential economic value of unique evolved artifacts. Building on this insight, this paper presents for the first time a Facebook game called Petalz in which players can share flowers they breed themselves with other players through a global marketplace. In particular, the market in this social game allows players to set the price of their evolved aesthetically-pleasing flowers in virtual currency. Furthermore, the transaction in which one player buys seeds from another creates a new social element that links the players in the transaction. The combination of unique user-generated content and social gaming in Petalz facilitates meaningful collaboration between users, positively influences the dynamics of the game, and opens new possibilities in digital entertainment.
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paper_title: Flocks, herds and schools: A distributed behavioral model

paper_content:

The aggregate motion of a flock of birds, a herd of land animals, or a school of fish is a beautiful and familiar part of the natural world. But this type of complex motion is rarely seen in computer animation. This paper explores an approach based on simulation as an alternative to scripting the paths of each bird individually. The simulated flock is an elaboration of a particle systems, with the simulated birds being the particles. The aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose their own course. Each simulated bird is implemented as an independent actor that navigates according to its local perception of the dynamic environment, the laws of simulated physics that rule its motion, and a set of behaviors programmed into it by the "animator." The aggregate motion of the simulated flock is the result of the dense interaction of the relatively simple behaviors of the individual simulated birds.
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paper_title: The Case for a Mixed-Initiative Collaborative Neuroevolution Approach

paper_content:

It is clear that the current attempts at using algorithms to create artificial neural networks have had mixed success at best when it comes to creating large networks and/or complex behavior. This should not be unexpected, as creating an artificial brain is essentially a design problem. Human design ingenuity still surpasses computational design for most tasks in most domains, including architecture, game design, and authoring literary fiction. This leads us to ask which the best way is to combine human and machine design capacities when it comes to designing artificial brains. Both of them have their strengths and weaknesses; for example, humans are much too slow to manually specify thousands of neurons, let alone the billions of neurons that go into a human brain, but on the other hand they can rely on a vast repository of common-sense understanding and design heuristics that can help them perform a much better guided search in design space than an algorithm. Therefore, in this paper we argue for a mixed-initiative approach for collaborative online brain building and present first results towards this goal.
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paper_title: Evolutionary Robotics on the Web with WebGL and Javascript

paper_content:

Web-based applications are highly accessible to users, providing rich, interactive content while eliminating the need to install software locally. However, evolutionary robotics (ER) has faced challenges in this domain as web-based technologies have not been amenable to 3D physics simulations. Traditionally, physics-based simulations require a local installation and a high degree of user knowledge to configure an environment, but the emergence of Javascript-based physics engines enables complex simulations to be executed in web browsers. These developments create opportunities for ER research to reach new audiences by increasing accessibility. In this work, we introduce two web-based tools we have built to facilitate the exchange of ideas with other researchers as well as outreach to K-12 students and the general public. The first tool is intended to distribute and exchange ER research results, while the second is a completely browser-based implementation of an ER environment.
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paper_title: Petalz: Search-Based Procedural Content Generation for the Casual Gamer

paper_content:

The impact of game content on the player experience is potentially more critical in casual games than in competitive games because of the diminished role of strategic or tactical diversions. Interestingly, until now procedural content generation (PCG) has nevertheless been investigated almost exclusively in the context of competitive, skills-based gaming. This paper therefore opens a new direction for PCG by placing it at the center of an entirely casual flower-breeding game platform called Petalz. That way, the behavior of players and their reactions to different game mechanics in a casual environment driven by PCG can be investigated. In particular, players in Petalz can: 1) trade their discoveries in a global marketplace; 2) respond to an incentive system that awards diversity; and 3) generate real-world 3-D replicas of their evolved flowers. With over 1900 registered online users and 38 646 unique evolved flowers, Petalz showcases the potential for PCG to enable these kinds of casual game mechanics, thus paving the way for continued innovation with PCG in casual gaming.
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paper_title: RoboGen: Robot Generation through Artificial Evolution

paper_content:

Science instructors from a wide range of disciplines agree that hands-on laboratory components of courses are pedagogically necessary (Freedman, 1997). However, certain shortcomings of current laboratory exercises have been pointed out by several authors (Mataric, 2004; Hofstein and Lunetta, 2004). The overarching theme of these analyses is that hands-on components of courses tend to be formulaic, closed-ended, and at times outdated. To address these issues, we envision a novel platform that is not only a didactic tool but is also an experimental testbed for users to play with different ideas in evolutionary robotics (Nolfi and Floreano, 2000), neural networks, physical simulation, 3D printing, mechanical assembly, and embedded processing. Here, we introduce RoboGen™: an open-source software and hardware platform designed for the joint evolution of robot morphologies and controllers a la Sims (1994); Lipson and Pollack (2000); Bongard and Pfeifer (2003). Robo- Gen has been designed specifically to allow evolved robots to be easily manufactured via widely available desktop 3D-printers, and the use of simple, open-source, low-cost, offthe- shelf electronic components. RoboGen features an evolution engine complete with a physics simulator, as well as utilities both for generating design files of body components for 3D printing, and for compiling neural-network controllers to run on an Arduino microcontroller board.
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paper_title: Learning Evolution and the Nature of Science LEARNING EVOLUTION AND THE NATURE OF SCIENCE USING EVOLUTIONARY COMPUTING AND ARTIFICIAL LIFE

paper_content:

Because evolution in natural systems happens so slowly, it is dif- ficult to design inquiry-based labs where students can experiment and observe evolution in the way they can when studying other phenomena. New research in evolutionary computation and artificial life provides a solution to this problem. This paper describes a new A-Life software environment - Avida-ED - in which undergraduate students can test evolutionary hypotheses directly using digital organisms that evolve on their own through the very mechanisms that Darwin discovered. APPRENDRE L'EVOLUTION ET LA NATURE DES SCIENCES AU MOYEN DU CALCUL
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paper_title: Evolving 3d morphology and behavior by competition

paper_content:

This article describes a system for the evolution and coevolution of virtual creatures that compete in physically simulated three-dimensional worlds. Pairs of individuals enter one-on-one contests in which they contend to gain control of a common resource. The winners receive higher relative fitness scores allowing them to survive and reproduce. Realistic dynamics simulation including gravity, collisions, and friction, restricts the actions to physically plausible behaviors. ::: ::: The morphology of these creatures and the neural systems for controlling their muscle forces are both genetically determined, and the morphology and behavior can adapt to each other as they evolve simultaneously. The genotypes are structured as directed graphs of nodes and connections, and they can efficiently but flexibly describe instructions for the development of creatures' bodies and control systems with repeating or recursive components. When simulated evolutions are performed with populations of competing creatures, interesting and diverse strategies and counterstrategies emerge.
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paper_title: Picbreeder: evolving pictures collaboratively online

paper_content:

Picbreeder is an online service that allows users to collaboratively evolve images. Like in other Interactive Evolutionary Computation (IEC) programs, users evolve images on Picbreeder by selecting ones that appeal to them to produce a new generation. However, Picbreeder also offers an online community in which to share these images, and most importantly, the ability to continue evolving others' images. Through this process of branching from other images, and through continually increasing image complexity made possible by the NeuroEvolution of Augmenting Topologies (NEAT) algorithm, evolved images proliferate unlike in any other current IEC systems. Participation requires no explicit talent from the users, thereby opening Picbreeder to the entire Internet community. This paper details how Picbreeder encourages innovation, featuring images that were collaboratively evolved.
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paper_title: Towards a virtual C. elegans: a framework for simulation and visualization of the neuromuscular system in a 3D physical environment.

paper_content:

The nematode C. elegans is the only animal with a known neuronal wiring diagram, or "connectome". During the last three decades, extensive studies of the C. elegans have provided wide-ranging data about it, but few systematic ways of inte- grating these data into a dynamic model have been put forward. Here we present a detailed demonstration of a virtual C. elegans aimed at integrating these data in the form of a 3D dynamic model operating in a simulated physical environment. Our current demonstration includes a realistic flexible worm body model, muscular system and a partially implemented ventral neural cord. Our virtual C. elegans demonstrates successful forward and backward locomotion when sending sinusoidal patterns of neuronal activity to groups of motor neurons. To account for the relatively slow propagation velocity and the attenuation of neuronal sig- nals, we introduced "pseudo neurons" into our model to simulate simplified neuronal dynamics. The pseudo neurons also pro- vide a good way of visualizing the nervous system's structure and activity dynamics.
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paper_title: Computer Viruses as Artificial Life

paper_content:

There has been considerable interest in computer viruses since they first appeared in 1981, and especially in the past few years as they have reached epidemic numbers in many personal computer environments. Viruses have been written about as a security problem, as a social problem, and as a possible means of performing useful tasks in a distributed computing environment. However, only recently have some scientists begun to ask if computer viruses are not a form of artificial life—a self-replicating organism. Simply because computer viruses do not exist as organic molecules may not be sufficient reason to dismiss the classification of this form of vandalware as a form of life. This paper begins with a description of how computer viruses operate and their history, and of the various ways computer viruses are structured. It then examines how viruses meet properties associated with life as defined by some researchers in the area of artificial life and self-organizing systems. The paper concludes with some comments directed toward the definition of artificially alive systems and experimentation.
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paper_title: Collective Learning and Semiotic Dynamics

paper_content:

We report on a case study in the emergence of a lexicon in a group of autonomous distributed agents situated and grounded in an open environment. Because the agents are autonomous, grounded, and situated, the possible words and possible meanings are not fixed but continuously change as the agents autonomously evolve their communication system and adapt it to novel situations. The case study shows that a complex semiotic dynamics unfolds and that generalisations present in the language are due to processes outside the agent.
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paper_title: Developing e-Bug web games to teach microbiology

paper_content:

As a complement to the e-Bug teaching pack, two e-Bug games were developed to provide content that aimedto entertain as well as to educate. A set of agreed learning outcomes (LOs) were provided by the scientiﬁc part-ners of the e-Bug Project and the games were developed using user-centred design techniques (the needs,wants and limitations of the potential game players were assessed at each stage of the design process).The e-Bug games were designed for two age groups: Junior (9–12 year olds); and Senior (13–15 year olds).A study using focus groups was done to gain an understanding as to the types of games enjoyed by thetarget users. According to the preliminary study, the Junior Game was developed as a platform game andthe Senior Game was developed as a story-based detective game. The Junior Game consists of ﬁve levels,each associated with a set of LOs. Similarly, the Senior Game consists of four missions, each comprising ﬁvestages using problem-based learning techniques and LOs. In this paper, the process of development foreach game is described in detail and an illustration is provided of how each game level or mission addressesthe target LOs.Development of the games used feedback acquired from children in four schools across the UK (Glasgow,London and two in Gloucester). The children were selected according to their willingness to participate.European Partners of the e-Bug Project also provided further support, translation and requests for modiﬁ-cations. The knowledge gained of LOs and further evaluation of the games is continuing, and preliminaryresults are in press. The ﬁnal versions of the games, translated into 11 European languages, are availableonline via www.e-bug.eu.Keywords: antibiotic resistance, hand washing, education web games, Internet intervention, problem-based learning (PBL)
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paper_title: EvoGrader: an online formative assessment tool for automatically evaluating written evolutionary explanations

paper_content:

EvoGrader is a free, online, on-demand formative assessment service designed for use in undergraduate biology classrooms. EvoGrader’s web portal is powered by Amazon’s Elastic Cloud and run with LightSIDE Lab’s open-source machine-learning tools. The EvoGrader web portal allows biology instructors to upload a response file (.csv) containing unlimited numbers of evolutionary explanations written in response to 86 different ACORNS (Assessing COntextual Reasoning about Natural Selection) instrument items. The system automatically analyzes the responses and provides detailed information about the scientific and naive concepts contained within each student’s response, as well as overall student (and sample) reasoning model types. Graphs and visual models provided by EvoGrader summarize class-level responses; downloadable files of raw scores (in .csv format) are also provided for more detailed analyses. Although the computational machinery that EvoGrader employs is complex, using the system is easy. Users only need to know how to use spreadsheets to organize student responses, upload files to the web, and use a web browser. A series of experiments using new samples of 2,200 written evolutionary explanations demonstrate that EvoGrader scores are comparable to those of trained human raters, although EvoGrader scoring takes 99% less time and is free. EvoGrader will be of interest to biology instructors teaching large classes who seek to emphasize scientific practices such as generating scientific explanations, and to teach crosscutting ideas such as evolution and natural selection. The software architecture of EvoGrader is described as it may serve as a template for developing machine-learning portals for other core concepts within biology and across other disciplines.
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paper_title: Evolving Neural Networks through Augmenting Topologies

paper_content:

An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. We present a method, NeuroEvolution of Augmenting Topologies (NEAT), which outperforms the best fixed-topology method on a challenging benchmark reinforcement learning task. We claim that the increased efficiency is due to (1) employing a principled method of crossover of different topologies, (2) protecting structural innovation using speciation, and (3) incrementally growing from minimal structure. We test this claim through a series of ablation studies that demonstrate that each component is necessary to the system as a whole and to each other. What results is significantly faster learning. NEAT is also an important contribution to GAs because it shows how it is possible for evolution to both optimize and complexify solutions simultaneously, offering the possibility of evolving increasingly complex solutions over generations, and strengthening the analogy with biological evolution.
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paper_title: Crucial factors in the origins of word-meaning

paper_content:

This work was carried out at the Sony Computer Science Laboratory in Paris and the VUB AI laboratory in Brussels (financed by a GOA grant).
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paper_title: Assessing Writing in MOOCs: Automated Essay Scoring and Calibrated Peer Review™

paper_content:

Joshua Brown, Adam Mikeal, and Alysha Clark provided substantial feedback that greatly enhanced the value and clarity of the information in this article. Abstract Two of the largest Massive Open Online Course (MOOC) organizations have chosen different methods for the way they will score and provide feedback on essays students submit. EdX, MIT and Harvard’s non-profit MOOC federation, recently announced that they will use a machine-based Automated Essay Scoring (AES) application to assess written work in their MOOCs. Coursera, a Stanford startup for MOOCs, has been skeptical of AES applications and therefore has held that it will use some form of human-based “calibrated peer review” to score and provide feedback on student writing. This essay reviews the relevant literature on AES and UCLA’s Calibrated Peer ReviewTM (CPR) product at a high level, outlines the capabilities and limitations of both AES and CPR, and provides a table and framework for comparing these forms of assessment of student writing in MOOCs. Stephen Balfour is an instructional associate professor of psychology and the Director of Information Technology for the College of Liberal Arts at Texas A&M University.
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paper_title: The ALife Zoo: cross-browser, platform-agnostic hosting of Artificial Life simulations

paper_content:

We describe a new approach to sharing software simulations that is of great potential benefit to Artificial Life researchers. youShare is an online collaborative facility that allows users to upload data, and software in the form of services. An attached execution environment allows services to be run over a heterogeneous cluster of compute nodes, where the service infrastructure guarantees that the service will be executed in the correct environment, and provide consistent results. It allows software to be made available as a service regardless of the operating system they run upon. This allows software to be maintained more easily, and to be available to all researchers with internet access. We demonstrate this by making three Artificial Life simulations available over the web: Tierra, Avida and Stringmol. These services form the foundation of an ALife “Zoo”, in which visitors can interact with ALife simulations for research and education. In addition, youShare offers a workflow facility whereby multiple services can be connected to create more complex tasks. We demonstrate the utility of this system in Artificial Life research via a workflow which calculates evolutionary activity for runs of Tierra and Stringmol.
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paper_title: Diversity from a Monoculture - Effects of Mutation-on-Copy in a String-Based Artificial Chemistry

paper_content:

We have developed an artificial chemistry that allows selfmaintaining molecular systems to mutate and exhibit innovative behaviour. The molecular species in the chemistry are defined by strings of symbols that specify both the binding affinity and the reaction. We define a replicase molecule that can copy any other molecule that binds at a particular region on the replicase. Molecules are copied on a symbolby-symbol basis. Occasional mis-copying of an individual symbol forms our mutation scheme. This paper describes the characteristics of the resulting evolutionary system. We ran 1,000 open-ended trials and observed an unexpectedly wide range of emergent phenomena, with many parallels to biological systems. We report these phenomena in qualitative terms, and give details of one of the most interesting among them: the emergence of co-dependent replicase hypercycles.
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paper_title: Steps Toward a Modular Library for Turning Any Evolutionary Domain into an Online Interactive Platform

paper_content:

Natural evolution inspires the fields of evolutionary computation (EC) and artificial life (ALife). A prominent feature of natural evolution is that it effectively never ends. However, most EC and ALife experiments are only run for several days or weeks at a time. Once an experiment concludes, reproducing, observing, or extending the results often requires considerable effort. In contrast, some Collaborative Interactive Evolution (CIE) systems, e.g. Picbreeder, were designed to preserve results as potential stepping stones to build upon later while taking advantage of human insight to solve challenging problems. Traditionally, building long-running and open experiments similar to Picbreeder presents a complex and timeconsuming software challenge. To reduce this challenge and thereby remove the barrier to situating almost any experiment within an interactive online framework, this paper presents the initial prototype for Worldwide Infrastructure for Neuroevolution (WIN). Built in the model of Picbreeder, WIN is a modular library for significantly reducing the complexity of creating fully persistent, online, and interactive evolutionary platforms for any new or existing domain. WIN Online, the public interface for WIN, provides an online collection of domains built with WIN that lets novice and expert users browse and meaningfully contribute to ongoing experiments. Two example experiments in this paper demonstrate WIN’s potential to quickly bootstrap any evolutionary domain with online and interactive capabilities.
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paper_title: Indirectly Encoded Sodarace for Artificial Life

paper_content:

The aim of this paper is to introduce a lightweight twodimensional domain for evolving diverse and interesting artificial creatures. The hope is that this domain will fill a need for such an easily-accessible option for researchers who wish to focus more on the evolutionary dynamics of artificial life scenarios than on building simulators and creature encodings. The proposed domain is inspired by Sodarace, a construction set for two-dimensional creatures made of masses and springs. However, unlike the original Sodarace, the indirectly encoded Sodarace (IESoR) system introduced in this paper allows evolution to discover a wide range of complex and regular ambulating creature morphologies by encoding them with compositional pattern producing networks (CPPNs), which are an established indirect encoding originally introduced for encoding large-scale neural networks. The result, demonstrated through a technique called novelty search with local competition (which are combined through multiobjective search), is that IESoR can discover a wide breadth of interesting and functional creatures, suggesting its potential utility for future experiments in artificial life.
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paper_title: COEL: A Web-based Chemistry Simulation Framework

paper_content:

The chemical reaction network (CRN) is a widely used formalism to describe macroscopic behavior of chemical systems. Available tools for CRN modelling and simulation require local access, installation, and often involve local le storage, which is susceptible to loss, lacks searchable structure, and does not support concurrency. Furthermore, simulations are often single-threaded, and user interfaces are non-trivial to use. Therefore there are signicant hurdles to conducting ecient and collaborative chemical research. In this paper, we introduce a new enterprise chemistry simulation framework, COEL, which addresses these issues. COEL is the rst web-based framework of its kind. A visually pleasing and intuitive user interface, simulations that run on a large computational grid, reliable database storage, and transactional services make COEL ideal for collaborative research and education. COEL’s most prominent features include ODE-based simulations of chemical reaction networks and multicompartment reaction networks, with rich options for user interactions with those networks. COEL provides DNA-strand displacement transformations and visualization (and is to our knowledge the rst CRN framework to do so), GA optimization of rate constants, expression validation, an application-wide plotting engine, and SBML/Octave/Matlab export. We also present an overview of the underlying software and technologies employed and describe the main architectural decisions driving our development. COEL is available at coel-sim.org for selected research teams only. We plan to provide a part of COEL’s functionality to the general public in the near future.
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paper_title: Twitter as Social Sensor: Dynamics and Structure in Major Sporting Events

paper_content:

Twitter often behaves like a “social sensor” in which users actively sense real-world events and spontaneously mention these events in cyberspace. Here, we study the temporal dynamics and structural properties of Twitter as a social sensor in major sporting events. By examining Japanese professional baseball games, we found that Twitter as a social sensor can immediately show reactions to positive and negative events by a burst of tweets, but only positive events induce a burst of retweets to follow. In addition, retweet networks during the baseball games exhibit clear polarization in user clusters depending on baseball teams, as well as a scalefree in-degree distribution. These empirical findings provide mechanistic insights into the emergence and evolution of social sensors.
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paper_title: Steps Toward a Modular Library for Turning Any Evolutionary Domain into an Online Interactive Platform

paper_content:

Natural evolution inspires the fields of evolutionary computation (EC) and artificial life (ALife). A prominent feature of natural evolution is that it effectively never ends. However, most EC and ALife experiments are only run for several days or weeks at a time. Once an experiment concludes, reproducing, observing, or extending the results often requires considerable effort. In contrast, some Collaborative Interactive Evolution (CIE) systems, e.g. Picbreeder, were designed to preserve results as potential stepping stones to build upon later while taking advantage of human insight to solve challenging problems. Traditionally, building long-running and open experiments similar to Picbreeder presents a complex and timeconsuming software challenge. To reduce this challenge and thereby remove the barrier to situating almost any experiment within an interactive online framework, this paper presents the initial prototype for Worldwide Infrastructure for Neuroevolution (WIN). Built in the model of Picbreeder, WIN is a modular library for significantly reducing the complexity of creating fully persistent, online, and interactive evolutionary platforms for any new or existing domain. WIN Online, the public interface for WIN, provides an online collection of domains built with WIN that lets novice and expert users browse and meaningfully contribute to ongoing experiments. Two example experiments in this paper demonstrate WIN’s potential to quickly bootstrap any evolutionary domain with online and interactive capabilities.
---
paper_title: The Art of Computer Virus Research and Defense

paper_content:

"Of all the computer-related books I've read recently, this one influenced my thoughts about security the most. There is very little trustworthy information about computer viruses. Peter Szor is one of the best virus analysts in the world and has the perfect credentials to write this book."-Halvar Flake, Reverse Engineer, SABRE Security GmbHSymantec's chief antivirus researcher has written the definitive guide to contemporary virus threats, defense techniques, and analysis tools. Unlike most books on computer viruses, The Art of Computer Virus Research and Defense is a reference written strictly for white hats: IT and security professionals responsible for protecting their organizations against malware. Peter Szor systematically covers everything you need to know, including virus behavior and classification, protection strategies, antivirus and worm-blocking techniques, and much more.Szor presents the state-of-the-art in both malware and protection, providing the full technical detail that professionals need to handle increasingly complex attacks. Along the way, he provides extensive information on code metamorphism and other emerging techniques, so you can anticipate and prepare for future threats.Szor also offers the most thorough and practical primer on virus analysis ever published-addressing everything from creating your own personal laboratory to automating the analysis process. This book's coverage includes Discovering how malicious code attacks on a variety of platforms Classifying malware strategies for infection, in-memory operation, self-protection, payload delivery, exploitation, and more Identifying and responding to code obfuscation threats: encrypted, polymorphic, and metamorphic Mastering empirical methods for analyzing malicious code-and what to do with what you learn Reverse-engineering malicious code with disassemblers, debuggers, emulators, and virtual machines Implementing technical defenses: scanning, code emulation, disinfection, inoculation, integrity checking, sandboxing, honeypots, behavior blocking, and much more Using worm blocking, host-based intrusion prevention, and network-level defense strategies © Copyright Pearson Education. All rights reserved.
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paper_title: Concepts of cooperation in artificial life

paper_content:

We have built some simple, but useful, cooperative artificial life agents. Based on this experience and by contrasting our work with computer viruses, we argue that artificial life (the simulation of life including evolution) can only remain reliably and indefinitely cooperative if it adheres to explicitly-specified social conventions. Breaking or neglecting these conventions results in systems that are worse than useless; in fact, malicious with respect to human social values. >
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paper_title: The EvoGrid - A Framework for Distributed Artificial Chemistry Cameo Simulations Supporting Computational Origins of Life Endeavors

paper_content:

The Evolution Grid, or EvoGrid is a computer simulation framework for distributed artificial chemistry (AC) supp orting computational origins of life (COoL) research. The EvoGrid consists of a number of small experiments running on sho rt time scales pruned by aggressive tree-branching search es supported by random parametric re-seeding and temporal backtracking. The EvoGrid is designed to converge upon the observation of “cameo” simulations of key pre-biotic or simple biological structures or behaviors. These cameo simula tions can then inform and feed larger AC simulations operating over biologically relevant time scales. In addition, the framework is designed to plug into a heterogeneous set of engines ranging from high fidelity molecular dynamics (MD) to more abstract AC techniques on the same set of data. The EvoGrid a lso provides shared web-based simulation management services and uniform, open standards for execution, storage an d data analysis. We conclude by describing the first prototype implementation of the EvoGrid, early results, next ste ps and open questions in this and other COoL endeavors.
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paper_title: A novel human-computer collaboration: combining novelty search with interactive evolution

paper_content:

Recent work on novelty and behavioral diversity in evolutionary computation has highlighted the potential disadvantage of driving search purely through objective means. This paper suggests that leveraging human insight during search can complement such novelty-driven approaches. In particular, a new approach called novelty-assisted interactive evolutionary computation (NA-IEC) combines human intuition with novelty search to facilitate the serendipitous discovery of agent behaviors in a deceptive maze. In this approach, the human user directs evolution by selecting what is interesting from the on-screen population of behaviors. However, unlike in typical IEC, the user can now request that the next generation be filled with novel descendants. The experimental results demonstrate that combining human insight with novelty search not only finds solutions significantly faster and at lower genomic complexities than fully-automated processes guided purely by fitness or novelty, but it also finds solutions faster than the traditional IEC approach. Such results add to the evidence that combining human users and automated processes creates a synergistic effect in the search for solutions.
---
paper_title: Service oriented evolutionary algorithms

paper_content:

This work presents a service oriented architecture for evolutionary algorithms, and an implementation of this architecture using a specific technology (called OSGiLiath). Service oriented architecture is a computational paradigm where users interact using services to increase the integration between systems. The presented abstract architecture is formed by loosely coupled, highly configurable and language-independent services. As an example of an implementation of this architecture, a complete process development using a specific service oriented technology is explained. With this implementation, less effort than classical development in integration, distribution mechanisms and execution time management has been attained. In addition, steps, ideas, advantages and disadvantages, and guidelines to create service oriented evolutionary algorithms are presented. Using existing software, or from scratch, researchers can create services to increase the interoperability in this area.
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paper_title: Designing robust volunteer-based evolutionary algorithms

paper_content:

This paper tackles the design of scalable and fault-tolerant evolutionary algorithms computed on volunteer platforms. These platforms aggregate computational resources from contributors all around the world. Given that resources may join the system only for a limited period of time, the challenge of a volunteer-based evolutionary algorithm is to take advantage of a large amount of computational power that in turn is volatile. The paper analyzes first the speed of convergence of massively parallel evolutionary algorithms. Then, it provides some guidance about how to design efficient policies to overcome the algorithmic loss of quality when the system undergoes high rates of transient failures, i.e. computers fail only for a limited period of time and then become available again. In order to provide empirical evidence, experiments were conducted for two well-known problems which require large population sizes to be solved, the first based on a genetic algorithm and the second on genetic programming. Results show that, in general, evolutionary algorithms undergo a graceful degradation under the stress of losing computing nodes. Additionally, new available nodes can also contribute to improving the search process. Despite losing up to 90 % of the initial computing resources, volunteer-based evolutionary algorithms can find the same solutions in a failure-prone as in a failure-free run.
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paper_title: Crowdseeding: A Novel Approach for Designing Bioinspired Machines

paper_content:

Crowdsourcing is a popular technique for distributing tasks to a group of anonymous workers over the web. Similarly, crowdseeding is any mechanism that extracts knowledge from the crowd, and then uses that knowledge to guide an automated process. Here we demonstrate a method that automatically distills features from a set of robot body plans designed by the crowd, and then uses those features to guide the automated design of robot body plans and controllers. This approach outperforms past work in which one feature was detected and distilled manually. This provides evidence that the crowd collectively possesses intuitions about the biomechanical advantages of certain body plans; we hypothesize that these intuitions derive from their experiences with biological organisms.
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paper_title: Metacreation: Art and Artificial Life

paper_content:

Artificial life, or a-life, is an interdisciplinary science focused on artificial systems that mimic the properties of living systems. In the 1990s, new media artists began appropriating and adapting the techniques of a-life science to create a-life art; Mitchell Whitelaw's Metacreation is the first detailed critical account of this new field of creative practice. A-life art responds to the increasing technologisation of living matter by creating works that seem to mutate, evolve, and respond with a life of their own. Pursuing a-life's promise of emergence, these artists produce not only artworks, but also generative and creative processes: here creation becomes metacreation. Whitelaw presents a-life art practice through four of its characteristic techniques and tendencies. "Breeders" use artificial evolution to generate images and forms, in the process altering the artist's creative agency. "Cybernatures" form complex, interactive systems, drawing the audience into artificial ecosystems. Other artists work in "Hardware," adapting Rodney Brooks's "bottom-up" robotics to create embodied autonomous agencies. The "Abstract Machines" of a-life art de-emphasise the biological analogy, using techniques such as cellular automata to investigate pattern, form and morphogenesis. In the book's concluding chapters Whitelaw surveys the theoretical discourses around a-life art, before finally examining emergence, a concept central to a-life, and key, it is argued, to a-life art.
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paper_title: Collective Creativity: Where we are and where we might go

paper_content:

Creativity is individual, and it is social. The social aspects of creativity have become of increasing interest as systems have emerged that mobilize large numbers of people to engage in creative tasks. We examine research related to collective intelligence and differentiate work on collective creativity from other collective activities by analyzing systems with respect to the tasks that are performed and the outputs that result. Three types of systems are discussed: games, contests and networks. We conclude by suggesting how systems that generate collective creativity can be improved and how new systems might be constructed.
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paper_title: Coupled Phases and Combinatorial Selection in Fluctuating Hydrothermal Pools: A Scenario to Guide Experimental Approaches to the Origin of Cellular Life

paper_content:

Hydrothermal fields on the prebiotic Earth are candidate environments for biogenesis. We propose a model in which molecular systems driven by cycles of hydration and dehydration in such sites undergo chemical evolution in dehydrated films on mineral surfaces followed by encapsulation and combinatorial selection in a hydrated bulk phase. The dehydrated phase can consist of concentrated eutectic mixtures or multilamellar liquid crystalline matrices. Both conditions organize and concentrate potential monomers and thereby promote polymerization reactions that are driven by reduced water activity in the dehydrated phase. In the case of multilamellar lipid matrices, polymers that have been synthesized are captured in lipid vesicles upon rehydration to produce a variety of molecular systems. Each vesicle represents a protocell, an “experiment” in a natural version of combinatorial chemistry. Two kinds of selective processes can then occur. The first is a physical process in which relatively stable molecular systems will be preferentially selected. The second is a chemical process in which rare combinations of encapsulated polymers form systems capable of capturing energy and nutrients to undergo growth by catalyzed polymerization. Given continued cycling over extended time spans, such combinatorial processes will give rise to molecular systems having the fundamental properties of life.
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paper_title: EvoSpace: a distributed evolutionary platform based on the tuple space model

paper_content:

This paper presents EvoSpace, a Cloud service for the development of distributed evolutionary algorithms. EvoSpace is based on the tuple space model, an associatively addressed memory space shared by several processes. Remote clients, called EvoWorkers, connect to EvoSpace and periodically take a subset of individuals from the global population, perform evolutionary operations on them, and return a set of new individuals. Several EvoWorkers carry out the evolutionary search in parallel and asynchronously, interacting with each other through the central repository. EvoSpace is designed to be domain independent and flexible, in the sense that in can be used with different types of evolutionary algorithms and applications. In this paper, a genetic algorithm is tested on the EvoSpace platform using a well-known benchmark problem, achieving promising results compared to a standard evolutionary system.
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paper_title: Using MapReduce Streaming for Distributed Life Simulation on the Cloud

paper_content:

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models 1 .
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paper_title: NodEO, a multi-paradigm distributed evolutionary algorithm platform in JavaScript

paper_content:

After more than fifteen years, JavaScript has finally risen as a popular language for implementing all kind of applications, from server-based to rich internet applications. The fact that it is implemented in the browser and in server-side tools makes it interesting for designing evolutionary algorithm frameworks that encompass both tiers, but besides, they allow a change in paradigm that goes beyond the canonical evolutionary algorithm. In this paper we will experiment with different architectures, client-server and peer to peer to assess which ones offer most advantages in terms of performance, scalability and ease of use for the computer scientist. All implementations have been released as open source, and besides showing that the concept of working with evolutionary algorithms in JavaScript can be done efficiently, we prove that a master-slave parallel architecture offers the best combination of time and algorithmic improvements in a parallel evolutionary algorithm that leverages JavaScript implementation features.
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paper_title: Modeling browser-based distributed evolutionary computation systems

paper_content:

From the era of big science we are back to the "do it yourself", where you do not have any money to buy clusters or subscribe to grids but still have algorithms that crave many computing nodes and need them to measure scalability. Fortunately, this coincides with the era of big data, cloud computing, and browsers that include JavaScript virtual machines. Those are the reasons why this paper will focus on two different aspects of volunteer or freeriding computing: first, the pragmatic: where to find those resources, which ones can be used, what kind of support you have to give them; and then, the theoretical: how evolutionary algorithms can be adapted to an environment in which nodes come and go, have different computing capabilities and operate in complete asynchrony of each other. We will examine the setup needed to create a very simple distributed evolutionary algorithm using JavaScript and then find a model of how users react to it by collecting data from several experiments featuring different classical benchmark functions.
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paper_title: Cloud-based evolutionary algorithms: An algorithmic study

paper_content:

This paper presents a cloud-computing based evolutionary algorithm using a synchronous storage service as pool for exchange information among population of solutions. The multi-computer was composed of several normal PCs or laptops connected via Wifi or Ethernet. In this work the effect of how the distributed evolutionary algorithm reached the solution when new PCs was added was tested whether that effect also translates to the algorithmic performance of the algorithm. To this end different (and hard) problems was addressed using the proposed multi-computer, analyzing the effects that the automatic load-balancing and synchronization had on the speed of algorithm successful, and analyzing how the number of evaluation per second increases when the multi-computer includes new nodes. The measure used for the analysis was number of evaluation per second which was increased when the multi-computer includes new nodes. The algorithm solved the proposed problems and it was viable to run it in homogeneous or heterogeneous platforms. The experiments includes two problems and different configuration for the distributed evolutionary algorithm in order to check the results of the algorithm for several rates of information exchange with the selected storage service. Results shows that the system is viable with homogeneous or heterogeneous nodes and there is no significative differences for the synchronous storage services we have tested. But when the problem is harder, and the threads of the algorithm does not stop for each information exchange (migration of individual from one population to another one), the differences of using a specific service became significative in terms of success of the algorithm.
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paper_title: Cyberbiogenesis and the EvoGrid: A Twenty-First Century Grand Challenge

paper_content:

The quest for the understanding of the mechanisms of the origin of life on Earth (and by implication elsewhere) could be greatly aided through a synthesis of computer simulation operating at the molecular level and the chemical replication of resultant models in the laboratory. The authors term this synthesis a cyberbiogenesis. The central technological challenge to computing such an “artificial origin of life” is to design computer models permitting de novo emergence of lifelike virtual structures and processes through multiple levels of complexity. This chapter explores cyberbiogenesis by investigating its antecedents, engages in a thought experiment rendered in computer graphics, examines results from an early implementation called the EvoGrid, and concludes by looking at the scientific, technical, religious, and philosophical conundrums presented by such an endeavor.
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paper_title: A Survey on Parallel and Distributed Multi-Agent Systems

paper_content:

Simulation has become an indispensable tool for researchers to explore systems without having recourse to real experiments. Depending on the characteristics of the modeled system, methods used to represent the system may vary. Multi-agent systems are, thus, often used to model and simulate complex systems. Whatever modeling type used, increasing the size and the precision of the model increases the amount of computation, requiring the use of parallel systems when it becomes too large. In this paper, we focus on parallel platforms that support multi-agent simulations. Our contribution is a survey on existing platforms and their evaluation in the context of high performance computing. We present a qualitative analysis, mainly based on platform properties, then a performance comparison using the same agent model implemented on each platform.
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paper_title: DrawCompileEvolve: Sparking Interactive Evolutionary Art with Human Creations

paper_content:

This paper presents DrawCompileEvolve, a web-based drawing tool which allows users to draw simple primitive shapes, group them together or define patterns in their groupings (e.g. symmetry, repetition). The user’s vector drawing is then compiled into an indirectly encoded genetic representation, which can be evolved interactively, allowing the user to change the image’s colors, patterns and ultimately transform it. The human artist has direct control while drawing the initial seed of an evolutionary run and indirect control while interactively evolving it, thus making DrawCompileEvolve a mixed-initiative art tool. Early results in this paper show the potential of DrawCompileEvolve to jump-start evolutionary art with meaningful drawings as well as the power of the underlying genetic representation to transform the user’s initial drawing into a different, yet potentially meaningful, artistic rendering.
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paper_title: Self-organization on social media: endo-exo bursts and baseline fluctuations

paper_content:

A salient dynamic property of social media is bursting behavior. In this paper, we study bursting behavior in terms of the temporal relation between a preceding baseline fluctuation and the successive burst response using a frequency time series of 3,000 keywords on Twitter. We found that there is a fluctuation threshold up to which the burst size increases as the fluctuation increases and that above the threshold, there appears a variety of burst sizes. We call this threshold the critical threshold. Investigating this threshold in relation to endogenous bursts and exogenous bursts based on peak ratio and burst size reveals that the bursts below this threshold are endogenously caused and above this threshold, exogenous bursts emerge. Analysis of the 3,000 keywords shows that all the nouns have both endogenous and exogenous origins of bursts and that each keyword has a critical threshold in the baseline fluctuation value to distinguish between the two. Having a threshold for an input value for activating the system implies that Twitter is an excitable medium. These findings are useful for characterizing how excitable a keyword is on Twitter and could be used, for example, to predict the response to particular information on social media.
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paper_title: Twitter as Social Sensor: Dynamics and Structure in Major Sporting Events

paper_content:

Twitter often behaves like a “social sensor” in which users actively sense real-world events and spontaneously mention these events in cyberspace. Here, we study the temporal dynamics and structural properties of Twitter as a social sensor in major sporting events. By examining Japanese professional baseball games, we found that Twitter as a social sensor can immediately show reactions to positive and negative events by a burst of tweets, but only positive events induce a burst of retweets to follow. In addition, retweet networks during the baseball games exhibit clear polarization in user clusters depending on baseball teams, as well as a scalefree in-degree distribution. These empirical findings provide mechanistic insights into the emergence and evolution of social sensors.
---
paper_title: Living Technology: Exploiting Life's Principles in Technology

paper_content:

The concept of living technology---that is, technology that is based on the powerful core features of life---is explained and illustrated with examples from artificial life software, reconfigurable and evolvable hardware, autonomously self-reproducing robots, chemical protocells, and hybrid electronic-chemical systems. We define primary (secondary) living technology according as key material components and core systems are not (are) derived from living organisms. Primary living technology is currently emerging, distinctive, and potentially powerful, motivating this review. We trace living technology's connections with artificial life (soft, hard, and wet), synthetic biology (top-down and bottom-up), and the convergence of nano-, bio-, information, and cognitive (NBIC) technologies. We end with a brief look at the social and ethical questions generated by the prospect of living technology.
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paper_title: Exploring Default Mode and Information Flow on the Web

paper_content:

Social networking services (e.g., Twitter, Facebook) are now major sources of World Wide Web (called “Web”) dynamics, together with Web search services (e.g., Google). These two types of Web services mutually influence each other but generate different dynamics. In this paper, we distinguish two modes of Web dynamics: the reactive mode and the default mode. It is assumed that Twitter messages (called “tweets”) and Google search queries react to significant social movements and events, but they also demonstrate signs of becoming self-activated, thereby forming a baseline Web activity. We define the former as the reactive mode and the latter as the default mode of the Web. In this paper, we investigate these reactive and default modes of the Web's dynamics using transfer entropy (TE). The amount of information transferred between a time series of 1,000 frequent keywords in Twitter and the same keywords in Google queries is investigated across an 11-month time period. Study of the information flow on Google and Twitter revealed that information is generally transferred from Twitter to Google, indicating that Twitter time series have some preceding information about Google time series. We also studied the information flow among different Twitter keywords time series by taking keywords as nodes and flow directions as edges of a network. An analysis of this network revealed that frequent keywords tend to become an information source and infrequent keywords tend to become sink for other keywords. Based on these findings, we hypothesize that frequent keywords form the Web's default mode, which becomes an information source for infrequent keywords that generally form the Web's reactive mode. We also found that the Web consists of different time resolutions with respect to TE among Twitter keywords, which will be another focal point of this paper.
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paper_title: Dynamic homeostasis in packet switching networks

paper_content:

In this study, we investigate the adaptation and robustness of a packet switching network (PSN), the fundamental architecture of the Internet. We claim that the adaptation introduced by a transmission control protocol congestion control mechanism is interpretable as the self-organization of complex itinerant behavior among many quasi-attracting states. To discuss this argument quantitatively, we study the adaptation of the Internet by simulating a PSN using ns-2. Our hypothesis is that the robustness and fragility of the Internet can be attributed to the inherent dynamics of the PSN feedback mechanism called the congestion window size, or cwnd. By varying the data input into the PSN system, we demonstrate the possible self-organization of attractors in cwnd temporal dynamics and discuss the adaptability and robustness of PSNs. The present study provides an example of Ashby's Law of Requisite Variety in action.
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paper_title: Robust design : a repertoire of biological, ecological, and engineering case studies

paper_content:

Robust Design brings together 16 chapters by an eminent group of authors in a wide range of fields presenting aspects of robustness in biological, ecological, and computational systems. The volume is the first to address robustness in biological, ecological, and computational systems. It is an outgrowth of a new research program on robustness at the Sante Fe Institute founded by the David and Lucile Packard Foundation. For those interested in complexity or interdisciplinary science, robustness is seen as currently among the most intellectually active and promising research areas with important applications in all fields of science, business, and economics.
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paper_title: Design Creativity Research: From the Individual to the Crowd

paper_content:

Research in design creativity has focused on individual creativity and on creativity in a collaborative or organizational setting. Collective design and crowdsourcing creativity differ from individual and collaborative creative design by building on the foundations of social computing so that individuals are motivated to contribute voluntarily. Research that improves our understanding and support for these phenomena is a trajectory from existing creativity and design research methods and models that study individuals and teams to studying crowds. Three directions for research in crowdsourcing creativity are: technology development, creative design processes, and evaluating creativity.
---
paper_title: Collective Creativity: Where we are and where we might go

paper_content:

Creativity is individual, and it is social. The social aspects of creativity have become of increasing interest as systems have emerged that mobilize large numbers of people to engage in creative tasks. We examine research related to collective intelligence and differentiate work on collective creativity from other collective activities by analyzing systems with respect to the tasks that are performed and the outputs that result. Three types of systems are discussed: games, contests and networks. We conclude by suggesting how systems that generate collective creativity can be improved and how new systems might be constructed.
---
paper_title: Human based genetic algorithm

paper_content:

A new class of genetic algorithms (GA) is presented. It is based on the idea of outsourcing, a popular trend in business. In a human based genetic algorithm (HBGA), all primary genetic operators are outsourced, i.e. delegated to external human agents. A totally outsourced genetic algorithm uses both human evaluation and the human ability of innovation. It is a multi-agent environment and the mediator of communication between multiple heterogenous agents. The advantage of this approach is its ability to address complex problems for which it is hard, not only to evaluate individuals, but to find a good representation for them. These qualities allow HBGA to process flows of information without knowledge of its particular structure and representation. The suggested conceptual approach can also be used as a general model and a way of thinking about different kinds of genetic algorithms.
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paper_title: Harnessing Crowds: Mapping the Genome of Collective Intelligence

paper_content:

Over the past decade, the rise of the Internet has enabled the emergence of surprising new forms of collective intelligence. Examples include Google, Wikipedia, Threadless, and many others. To take advantage of the possibilities these new systems represent, it is necessary to go beyond just seeing them as a fuzzy collection of "cool" ideas. What is needed is a deeper understanding of how these systems work. This article offers a new framework to help provide that understanding. It identifies the underlying building blocks - to use a biological metaphor, the "genes" - at the heart of collective intelligence systems. These genes are defined by the answers to two pairs of key questions: - Who is performing the task? Why are they doing it? - What is being accomplished? How is it being done? The paper goes on to list the genes of collective intelligence - the possible answers to these key questions - and shows how combinations of genes comprise a "genome" that characterizes each collective intelligence system. In addition, the paper describes the conditions under which each gene is useful and the possibilities for combining and re-combining these genes to harness crowds effectively. Using this framework, managers can systematically consider many possible combinations of genes as they seek to develop new collective intelligence systems.
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paper_title: Human computation: a survey and taxonomy of a growing field

paper_content:

The rapid growth of human computation within research and industry has produced many novel ideas aimed at organizing web users to do great things. However, the growth is not adequately supported by a framework with which to understand each new system in the context of the old. We classify human computation systems to help identify parallels between different systems and reveal "holes" in the existing work as opportunities for new research. Since human computation is often confused with "crowdsourcing" and other terms, we explore the position of human computation with respect to these related topics.
---
paper_title: A novel human-computer collaboration: combining novelty search with interactive evolution

paper_content:

Recent work on novelty and behavioral diversity in evolutionary computation has highlighted the potential disadvantage of driving search purely through objective means. This paper suggests that leveraging human insight during search can complement such novelty-driven approaches. In particular, a new approach called novelty-assisted interactive evolutionary computation (NA-IEC) combines human intuition with novelty search to facilitate the serendipitous discovery of agent behaviors in a deceptive maze. In this approach, the human user directs evolution by selecting what is interesting from the on-screen population of behaviors. However, unlike in typical IEC, the user can now request that the next generation be filled with novel descendants. The experimental results demonstrate that combining human insight with novelty search not only finds solutions significantly faster and at lower genomic complexities than fully-automated processes guided purely by fitness or novelty, but it also finds solutions faster than the traditional IEC approach. Such results add to the evidence that combining human users and automated processes creates a synergistic effect in the search for solutions.
---
paper_title: Studying Collective Human Decision Making and Creativity with Evolutionary Computation

paper_content:

We report a summary of our interdisciplinary research project "Evolutionary Perspective on Collective Decision Making" that was conducted through close collaboration between computational, organizational, and social scientists at Binghamton University. We redefined collective human decision making and creativity as evolution of ecologies of ideas, where populations of ideas evolve via continual applications of evolutionary operators such as reproduction, recombination, mutation, selection, and migration of ideas, each conducted by participating humans. Based on this evolutionary perspective, we generated hypotheses about collective human decision making, using agent-based computer simulations. The hypotheses were then tested through several experiments with real human subjects. Throughout this project, we utilized evolutionary computation EC in non-traditional ways-1 as a theoretical framework for reinterpreting the dynamics of idea generation and selection, 2 as a computational simulation model of collective human decision-making processes, and 3 as a research tool for collecting high-resolution experimental data on actual collaborative design and decision making from human subjects. We believe our work demonstrates untapped potential of EC for interdisciplinary research involving human and social dynamics.
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paper_title: Artificial life programming in the robust-first attractor

paper_content:

Despite mounting awareness of the liabilities of deterministic CPU and RAM computing, across industry and academia there remains little clear vision of a fundamental, generalpurpose alternative. To obtain indefinitely scalable computer architectures offering improved robustness and security, we have advocated a realignment of the roles of hardware and software based on artificial life principles. In this paper we propose an active media computational abstraction to underlie such a hardware-software renegotiation. The active media framework is much in the spirit of probabilistic cellular automata, but designed for indefinite scalability and serious programmability, rather than simplicity and analytic tractability. We discuss active media programming techniques based on living systems principles, and present anecdotal data from sample programs to introduce a new programming language called ulam, that we are developing as an underlying language for active media.
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paper_title: From Here to Eternity—The Theory and Practice of a Really Long Experiment

paper_content:

In February 1988, Richard Lenski set up 12 replicate populations of a single genotype of Escherichia coli in a simple nutrient medium. He has been following their evolution ever since. Here, Lenski answers provocative questions from Jeremy Fox about his iconic "Long-Term Evolution Experiment" (LTEE). The LTEE is a remarkable case study of the interplay of determinism and chance in evolution—and in the conduct of science.
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paper_title: Innovation Engines: Automated Creativity and Improved Stochastic Optimization via Deep Learning

paper_content:

The Achilles Heel of stochastic optimization algorithms is getting trapped on local optima. Novelty Search avoids this problem by encouraging a search in all interesting directions. That occurs by replacing a performance objective with a reward for novel behaviors, as defined by a human-crafted, and often simple, behavioral distance function. While Novelty Search is a major conceptual breakthrough and outperforms traditional stochastic optimization on certain problems, it is not clear how to apply it to challenging, high-dimensional problems where specifying a useful behavioral distance function is difficult. For example, in the space of images, how do you encourage novelty to produce hawks and heroes instead of endless pixel static? Here we propose a new algorithm, the Innovation Engine, that builds on Novelty Search by replacing the human-crafted behavioral distance with a Deep Neural Network (DNN) that can recognize interesting differences between phenotypes. The key insight is that DNNs can recognize similarities and differences between phenotypes at an abstract level, wherein novelty means interesting novelty. For example, a novelty pressure in image space does not explore in the low-level pixel space, but instead creates a pressure to create new types of images (e.g. churches, mosques, obelisks, etc.). Here we describe the long-term vision for the Innovation Engine algorithm, which involves many technical challenges that remain to be solved. We then implement a simplified version of the algorithm that enables us to explore some of the algorithm's key motivations. Our initial results, in the domain of images, suggest that Innovation Engines could ultimately automate the production of endless streams of interesting solutions in any domain: e.g. producing intelligent software, robot controllers, optimized physical components, and art.
---
paper_title: Automated Evolution of Interesting Images

paper_content:

Note: The Humanities and ALife -- Best Presentation Award Winner. Reference EPFL-CONF-191282 Record created on 2013-12-13, modified on 2017-05-10
---

Title: WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web

Section 1: Introduction
Description 1: Discuss the emerging trend of using web technology in artificial life (ALife) research, the influence of HTML5, key projects and initiatives in WebAL, and the motivation for this review article.

Section 2: Review Scope and Methodology
Description 2: Define the scope and methodology used for collecting and analyzing the materials reviewed in this article.

Section 3: The Precursors to WebAL
Description 3: Explore significant antecedents to WebAL, such as early network technology applications in arts, computer games, distributed systems, and evolutionary computing.

Section 4: The 1990s: Early WebAL
Description 4: Review the first WebAL systems from the 1990s, describing key projects and their impacts on the field.

Section 5: The 2000s: WebAL Develops
Description 5: Discuss the evolution of WebAL through the 2000s, highlighting advancements in web technologies and their influence on WebAL projects.

Section 6: Current State of the Art
Description 6: Examine recent developments and current projects, focusing on evolutionary art and design, games, science and education, frameworks for WebAL, and new directions.

Section 7: Emerging Themes and Future Directions
Description 7: Identify important emerging themes in WebAL and predict possible future directions of research and development.

Section 8: Conclusion
Description 8: Summarize the review, emphasizing the advancements over the past 21 years, the current landscape, and the future potential of WebAL research.