title: Symbolic artificial intelligence

text: Neural networks, a sub-symbolic approach, had been pursued from early days and was to reemerge strongly in 2012. Early examples are Rosenblatt's perceptron learning work, the backpropagation work of Rumelhart, Hinton and Williams, and work in convolutional neural networks by LeCun et al. in 1989. However, neural networks were not viewed as successful until about 2012: "Until Big Data became commonplace, the general consensus in the Al community was that the so-called neural-network approach was hopeless. Systems just didn't work that well, compared to other methods. ... A revolution came in 2012, when a number of people, including a team of researchers working with Hinton, worked out a way to use the power of GPUs to enormously increase the power of neural networks." Over the next several years, deep learning had spectacular success in handling vision, speech recognition, speech synthesis, image generation, and machine translation. However, since 2020, as inherent difficulties with bias, explanation, comprehensibility, and robustness became more apparent with deep learning approaches; an increasing number of AI researchers have called for combining the best of both the symbolic and neural network approaches and addressing areas that both approaches have difficulty with, such as common-sense reasoning.


title: Symbolic artificial intelligence

text: The symbolic approach was succinctly expressed in the "physical symbol systems hypothesis" proposed by Newell and Simon in 1976:


title: Symbolic artificial intelligence

text: to describe that high-performance in a specific domain required both general and highly domain-specific knowledge. Ed Feigenbaum and Doug Lenat called this The Knowledge Principle:


title: Symbolic artificial intelligence

text: Finally, with the rise of deep learning, the symbolic AI approach has been compared to deep learning as complementary "...with parallels having been drawn many times by AI researchers between Kahneman's research on human reasoning and decision making – reflected in his book "Thinking, Fast and Slow" – and the so-called "AI systems 1 and 2", which would in principle be modelled by deep learning and symbolic reasoning, respectively." In this view, symbolic reasoning is more apt for deliberative reasoning, planning, and explanation while deep learning is more apt for fast pattern recognition in perceptual applications with noisy data.


title: Symbolic artificial intelligence

text: A short history of symbolic AI to the present day follows below. Time periods and titles are drawn from Henry Kautz's 2020 AAAI Robert S. Engelmore Memorial Lecture and the longer Wikipedia article on the History of AI, with dates and titles differing slightly for increased clarity.


title: Symbolic artificial intelligence

text: Success at early attempts in AI occurred in three main areas: artificial neural networks, knowledge representation, and heuristic search, contributing to high expectations. This section summarizes Kautz's reprise of early AI history.


title: Symbolic artificial intelligence

text: Cybernetic approaches attempted to replicate the feedback loops between animals and their environments. A robotic turtle, with sensors, motors for driving and steering, and seven vacuum tubes for control, based on a preprogrammed neural net, was built as early as 1948. This work can be seen as an early precursor to later work in neural networks, reinforcement learning, and situated robotics.


title: Symbolic artificial intelligence

text: An important early symbolic AI program was the Logic theorist, written by Allen Newell, Herbert Simon and Cliff Shaw in 1955–56, as it was able to prove 38 elementary theorems from Whitehead and Russell's Principia Mathematica. Newell, Simon, and Shaw later generalized this work to create a domain-independent problem solver, GPS (General Problem Solver). GPS solved problems represented with formal operators via state-space search using means-ends analysis.


title: Symbolic artificial intelligence

text: During the 1960s, symbolic approaches achieved great success at simulating intelligent behavior in structured environments such as game-playing, symbolic mathematics, and theorem-proving. AI research was centered in three institutions in the 1960s: Carnegie Mellon University, Stanford, MIT and (later) University of Edinburgh. Each one developed its own style of research. Earlier approaches based on cybernetics or artificial neural networks were abandoned or pushed into the background.


title: Symbolic artificial intelligence

text: Herbert Simon and Allen Newell studied human problem-solving skills and attempted to formalize them, and their work laid the foundations of the field of artificial intelligence, as well as cognitive science, operations research and management science. Their research team used the results of psychological experiments to develop programs that simulated the techniques that people used to solve problems. This tradition, centered at Carnegie Mellon University would eventually culminate in the development of the Soar architecture in the middle 1980s.


title: Symbolic artificial intelligence

text: In addition to the highly-specialized domain-specific kinds of knowledge that we will see later used in expert systems, early symbolic AI researchers discovered another more general application of knowledge. These were called heuristics, rules of thumb that guide a search in promising directions: "How can non-enumerative search be practical when the underlying problem is exponentially hard? The approach advocated by Simon and Newell is to employ heuristics: fast algorithms that may fail on some inputs or output suboptimal solutions." Another important advance was to find a way to apply these heuristics that guarantees a solution will be found, if there is one, not withstanding the occasional fallibility of heuristics: "The A* algorithm provided a general frame for complete and optimal heuristically guided search. A* is used as a subroutine within practically every AI algorithm today but is still no magic bullet; its guarantee of completeness is bought at the cost of worst-case exponential time.


title: Symbolic artificial intelligence

text: Early work covered both applications of formal reasoning emphasizing first-order logic, along with attempts to handle common-sense reasoning in a less formal manner.


title: Symbolic artificial intelligence

text: Unlike Simon and Newell, John McCarthy felt that machines did not need to simulate the exact mechanisms of human thought, but could instead try to find the essence of abstract reasoning and problem-solving with logic, regardless of whether people used the same algorithms.


title: Symbolic artificial intelligence

text: His laboratory at Stanford (SAIL) focused on using formal logic to solve a wide variety of problems, including knowledge representation, planning and learning.


title: Symbolic artificial intelligence

text: Logic was also the focus of the work at the University of Edinburgh and elsewhere in Europe which led to the development of the programming language Prolog and the science of logic programming.


title: Symbolic artificial intelligence

text: Researchers at MIT (such as Marvin Minsky and Seymour Papert) found that solving difficult problems in vision and natural language processing required ad hoc solutions—they argued that no simple and general principle (like logic) would capture all the aspects of intelligent behavior. Roger Schank described their "anti-logic" approaches as "scruffy" (as opposed to the "neat" paradigms at CMU and Stanford).


title: Symbolic artificial intelligence

text: Commonsense knowledge bases (such as Doug Lenat's Cyc) are an example of "scruffy" AI, since they must be built by hand, one complicated concept at a time.


title: Symbolic artificial intelligence

text: As limitations with weak, domain-independent methods became more and more apparent, researchers from all three traditions began to build knowledge into AI applications. The knowledge revolution was driven by the realization that knowledge underlies high-performance, domain-specific AI applications.


title: Symbolic artificial intelligence

text: This "knowledge revolution" led to the development and deployment of expert systems (introduced by Edward Feigenbaum), the first commercially successful form of AI software.


title: Symbolic artificial intelligence

text: DENDRAL is considered the first expert system that relied on knowledge-intensive problem-solving. It is described below, by Ed Feigenbaum, from a Communications of the ACM interview, Interview with Ed Feigenbaum:


title: Symbolic artificial intelligence

text: The other expert systems mentioned above came after DENDRAL. MYCIN exemplifies the classic expert system architecture of a knowledge-base of rules coupled to a symbolic reasoning mechanism, including the use of certainty factors to handle uncertainty. GUIDON shows how an explicit knowledge base can be repurposed for a second application, tutoring, and is an example of an intelligent tutoring system, a particular kind of knowledge-based application. Clancey showed that it was not sufficient simply to use MYCIN's rules for instruction, but that he also needed to add rules for dialogue management and student modeling. XCON is significant because of the millions of dollars it saved DEC, which triggered the expert system boom where most all major corporations in the US had expert systems groups, with the aim to capture corporate expertise, preserve it, and automate it:


title: Symbolic artificial intelligence

text: Chess expert knowledge was encoded in Deep Blue. In 1996, this allowed IBM's Deep Blue, with the help of symbolic AI, to win in a game of chess against the world champion at that time, Garry Kasparov.


title: Symbolic artificial intelligence

text: A key component of the system architecture for all expert systems is the knowledge base, which stores facts and rules for problem-solving.


title: Symbolic artificial intelligence

text: The simplest approach for an expert system knowledge base is simply a collection or network of production rules. Production rules connect symbols in a relationship similar to an If-Then statement. The expert system processes the rules to make deductions and to determine what additional information it needs, i.e. what questions to ask, using human-readable symbols. For example, OPS5, CLIPS and their successors Jess and Drools operate in this fashion.


title: Symbolic artificial intelligence

text: Expert systems can operate in either a forward chaining – from evidence to conclusions – or backward chaining – from goals to needed data and prerequisites – manner. More advanced knowledge-based systems, such as Soar can also perform meta-level reasoning, that is reasoning about their own reasoning in terms of deciding how to solve problems and monitoring the success of problem-solving strategies.


title: Symbolic artificial intelligence

text: Blackboard systems are a second kind of knowledge-based or expert system architecture. They model a community of experts incrementally contributing, where they can, to solve a problem. The problem is represented in multiple levels of abstraction or alternate views. The experts (knowledge sources) volunteer their services whenever they recognize they can make a contribution. Potential problem-solving actions are represented on an agenda that is updated as the problem situation changes. A controller decides how useful each contribution is, and who should make the next problem-solving action. One example, the BB1 blackboard architecture was originally inspired by studies of how humans plan to perform multiple tasks in a trip. An innovation of BB1 was to apply the same blackboard model to solving its own control problem, i.e., its controller performed meta-level reasoning with knowledge sources that monitored how well a plan or the problem-solving was proceeding, and could switch from one strategy to another as conditions – such as goals or times – changed. BB1 was applied in multiple domains: construction site planning, intelligent tutoring systems, and real-time patient monitoring.


title: Symbolic artificial intelligence

text: At the height of the AI boom, companies such as Symbolics, LMI, and Texas Instruments were selling LISP machines specifically targeted to accelerate the development of AI applications and research. In addition, several artificial intelligence companies, such as Teknowledge and Inference Corporation, were selling expert system shells, training, and consulting to corporations.


title: Symbolic artificial intelligence

text: One statistical approach, Hidden Markov Models, had already been popularized in the 1980s for speech recognition work. Subsequently, in 1988, Judea Pearl popularized the use of Bayesian Networks as a sound but efficient way of handling uncertain reasoning with his publication of the book Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. and Bayesian approaches were applied successfully in expert systems. Even later, in the 1990s, statistical relational learning, an approach that combines probability with logical formulas, allowed probability to be combined with first-order logic, e.g., with either Markov Logic Networks or Probabilistic Soft Logic.


title: Symbolic artificial intelligence

text: Other, non-probabilistic extensions to first-order logic to support were also tried. For example, non-monotonic reasoning could be used with truth maintenance systems. A truth maintenance system tracked assumptions and justifications for all inferences. It allowed inferences to be withdrawn when assumptions were found out to be incorrect or a contradiction was derived. Explanations could be provided for an inference by explaining which rules were applied to create it and then continuing through underlying inferences and rules all the way back to root assumptions. Lofti Zadeh had introduced a different kind of extension to handle the representation of vagueness. For example, in deciding how "heavy" or "tall" a man is, there is frequently no clear "yes" or "no" answer, and a predicate for heavy or tall would instead return values between 0 and 1. Those values represented to what degree the predicates were true. His fuzzy logic further provided a means for propagating combinations of these values through logical formulas.


title: Symbolic artificial intelligence

text: Symbolic machine learning approaches were investigated to address the knowledge acquisition bottleneck. One of the earliest is Meta-DENDRAL. Meta-DENDRAL used a generate-and-test technique to generate plausible rule hypotheses to test against spectra. Domain and task knowledge reduced the number of candidates tested to a manageable size. Feigenbaum described Meta-DENDRAL as


title: Symbolic artificial intelligence

text: In contrast to the knowledge-intensive approach of Meta-DENDRAL, Ross Quinlan invented a domain-independent approach to statistical classification, decision tree learning, starting first with ID3 and then later extending its capabilities to C4.5. The decision trees created are glass box, interpretable classifiers, with human-interpretable classification rules.


title: Symbolic artificial intelligence

text: Advances were made in understanding machine learning theory, too. Tom Mitchell introduced version space learning which describes learning as search through a space of hypotheses, with upper, more general, and lower, more specific, boundaries encompassing all viable hypotheses consistent with the examples seen so far. More formally, Valiant introduced Probably Approximately Correct Learning (PAC Learning), a framework for the mathematical analysis of machine learning.


title: Symbolic artificial intelligence

text: Symbolic machine learning encompassed more than learning by example. E.g., John Anderson provided a cognitive model of human learning where skill practice results in a compilation of rules from a declarative format to a procedural format with his ACT-R cognitive architecture. For example, a student might learn to apply "Supplementary angles are two angles whose measures sum 180 degrees" as several different procedural rules. E.g., one rule might say that if X and Y are supplementary and you know X, then Y will be 180 - X. He called his approach "knowledge compilation". ACT-R has been used successfully to model aspects of human cognition, such as learning and retention. ACT-R is also used in intelligent tutoring systems, called cognitive tutors, to successfully teach geometry, computer programming, and algebra to school children.


title: Symbolic artificial intelligence

text: Inductive logic programming was another approach to learning that allowed logic programs to be synthesized from input-output examples. E.g., Ehud Shapiro's MIS (Model Inference System) could synthesize Prolog programs from examples. John R. Koza applied genetic algorithms to program synthesis to create genetic programming, which he used to synthesize LISP programs. Finally, Manna and Waldinger provided a more general approach to program synthesis that synthesizes a functional program in the course of proving its specifications to be correct.


title: Symbolic artificial intelligence

text: As an alternative to logic, Roger Schank introduced case-based reasoning (CBR). The CBR approach outlined in his book, Dynamic Memory, focuses first on remembering key problem-solving cases for future use and generalizing them where appropriate. When faced with a new problem, CBR retrieves the most similar previous case and adapts it to the specifics of the current problem. Another alternative to logic, genetic algorithms and genetic programming are based on an evolutionary model of learning, where sets of rules are encoded into populations, the rules govern the behavior of individuals, and selection of the fittest prunes out sets of unsuitable rules over many generations.


title: Symbolic artificial intelligence

text: Symbolic machine learning was applied to learning concepts, rules, heuristics, and problem-solving. Approaches, other than those above, include:


title: Symbolic artificial intelligence

text: Neuro-symbolic AI attempts to integrate neural and symbolic architectures in a manner that addresses strengths and weaknesses of each, in a complementary fashion, in order to support robust AI capable of reasoning, learning, and cognitive modeling. As argued by Valiant and many others, the effective construction of rich computational cognitive models demands the combination of sound symbolic reasoning and efficient (machine) learning models. Gary Marcus, similarly, argues that: "We cannot construct rich cognitive models in an adequate, automated way without the triumvirate of hybrid architecture, rich prior knowledge, and sophisticated techniques for reasoning.", and in particular:


title: Symbolic artificial intelligence

text: "To build a robust, knowledge-driven approach to AI we must have the machinery of symbol-manipulation in our toolkit. Too much of useful knowledge is abstract to make do without tools that represent and manipulate abstraction, and to date, the only machinery that we know of that can manipulate such abstract knowledge reliably is the apparatus of symbol-manipulation."


title: Symbolic artificial intelligence

text: Henry Kautz, Francesca Rossi, and Bart Selman have also argued for a synthesis. Their arguments are based on a need to address the two kinds of thinking discussed in Daniel Kahneman's book, "Thinking, Fast and Slow". Kahneman describes human thinking as having two components, System 1 and System 2. System 1 is fast, automatic, intuitive and unconscious. System 2 is slower, step-by-step, and explicit. System 1 is the kind used for pattern recognition while System 2 is far better suited for planning, deduction, and deliberative thinking. In this view, deep learning best models the first kind of thinking while symbolic reasoning best models the second kind and both are needed.


title: Symbolic artificial intelligence

text: Garcez describes research in this area as being ongoing for at least the past twenty years, dating from his 2002 book on neurosymbolic learning systems. A series of workshops on neuro-symbolic reasoning has been held every year since 2005, see http://www.neural-symbolic.org/ for details.


title: Symbolic artificial intelligence

text: In their 2015 paper, Neural-Symbolic Learning and Reasoning: Contributions and Challenges, Garcez et al. argue that:


title: Symbolic artificial intelligence

text: Approaches for integration are varied. Henry Kautz's taxonomy of neuro-symbolic architectures, along with some examples, follows:


title: Symbolic artificial intelligence

text: This section provides an overview of techniques and contributions in an overall context leading to many other, more detailed articles in Wikipedia. Sections on Machine Learning and Uncertain Reasoning are covered earlier in the history section.


title: Symbolic artificial intelligence

text: The key AI programming language in the US during the last symbolic AI boom period was LISP. LISP is the second oldest programming language after FORTRAN and was created in 1958 by John McCarthy. LISP provided the first read-eval-print loop to support rapid program development. Compiled functions could be freely mixed with interpreted functions. Program tracing, stepping, and breakpoints were also provided, along with the ability to change values or functions and continue from breakpoints or errors. It had the first self-hosting compiler, meaning that the compiler itself was originally written in LISP and then ran interpretively to compile the compiler code.


title: Symbolic artificial intelligence

text: Programs were themselves data structures that other programs could operate on, allowing the easy definition of higher-level languages.


title: Symbolic artificial intelligence

text: In contrast to the US, in Europe the key AI programming language during that same period was Prolog. Prolog provided a built-in store of facts and clauses that could be queried by a read-eval-print loop. The store could act as a knowledge base and the clauses could act as rules or a restricted form of logic. As a subset of first-order logic Prolog was based on Horn clauses with a closed-world assumption -- any facts not known were considered false -- and a unique name assumption for primitive terms -- e.g., the identifier barack_obama was considered to refer to exactly one object. Backtracking and unification are built-in to Prolog.


title: Symbolic artificial intelligence

text: Alain Colmerauer and Philippe Roussel are credited as the inventors of Prolog. Prolog is a form of logic programming, which was invented by Robert Kowalski. Its history was also influenced by Carl Hewitt's PLANNER, an assertional database with pattern-directed invocation of methods. For more detail see the section on the origins of Prolog in the PLANNER article.


title: Symbolic artificial intelligence

text: Prolog is also a kind of declarative programming. The logic clauses that describe programs are directly interpreted to run the programs specified. No explicit series of actions is required, as is the case with imperative programming languages.


title: Symbolic artificial intelligence

text: Japan championed Prolog for its Fifth Generation Project, intending to build special hardware for high performance. Similarly, LISP machines were built to run LISP, but as the second AI boom turned to bust these companies could not compete with new workstations that could now run LISP or Prolog natively at comparable speeds. See the history section for more detail.


title: Symbolic artificial intelligence

text: Smalltalk was another influential AI programming language. For example it introduced metaclasses and, along with Flavors and CommonLoops, influenced the Common Lisp Object System, or (CLOS), that is now part of Common Lisp, the current standard Lisp dialect. CLOS is a Lisp-based object-oriented system that allows multiple inheritance, in addition to incremental extensions to both classes and metaclasses, thus providing a run-time meta-object protocol.


title: Symbolic artificial intelligence

text: For other AI programming languages see this list of programming languages for artificial intelligence. Currently, Python, a multi-paradigm programming language, is the most popular programming language, partly due to its extensive package library that supports data science, natural language processing, and deep learning. Python includes a read-eval-print loop, functional elements such as higher-order functions, and object-oriented programming that includes metaclasses.


title: Symbolic artificial intelligence

text: Search arises in many kinds of problem solving, including planning, constraint satisfaction, and playing games such as checkers, chess, and go. The best known AI-search tree search algorithms are breadth-first search, depth-first search, A*, and Monte Carlo Search. Key search algorithms for Boolean satisfiability are WalkSAT, conflict-driven clause learning, and the DPLL algorithm. For adversarial search when playing games, alpha-beta pruning, branch and bound, and minimax were early contributions.


title: Symbolic artificial intelligence

text: Multiple different approaches to represent knowledge and then reason with those representations have been investigated. Below is a quick overview of approaches to knowledge representation and automated reasoning.


title: Symbolic artificial intelligence

text: Semantic networks, conceptual graphs, frames, and logic are all approaches to modeling knowledge such as domain knowledge, problem-solving knowledge, and the semantic meaning of language. Ontologies model key concepts and their relationships in a domain. Example ontologies are YAGO, WordNet, and DOLCE. DOLCE is an example of an upper ontology that can be used for any domain while WordNet is a lexical resource that can also be viewed as an ontology. YAGO incorporates WordNet as part of its ontology, to align facts extracted from Wikipedia with WordNet synsets. The Disease Ontology is an example of a medical ontology currently being used.


title: Symbolic artificial intelligence

text: Description logic is a logic for automated classification of ontologies and for detecting inconsistent classification data. OWL is a language used to represent ontologies with description logic. Protégé is a ontology editor that can read in OWL ontologies and then check consistency with deductive classifiers such as such as HermiT.


title: Symbolic artificial intelligence

text: First-order logic is more general than description logic. The automated theorem provers discussed below can prove theorems in first-order logic. Horn clause logic is more restricted than first-order logic and is used in logic programming languages such as Prolog. Extensions to first-order logic include temporal logic, to handle time; epistemic logic, to reason about agent knowledge; modal logic, to handle possibility and necessity; and probabilistic logics to handle logic and probability together.


title: Symbolic artificial intelligence

text: Prover9 can be used in conjunction with the Mace4 model checker. ACL2 is a theorem prover that can handle proofs by induction and is a descendant of the Boyer-Moore Theorem Prover, also known as Nqthm.


title: Symbolic artificial intelligence

text: Knowledge-based systems have an explicit knowledge base, typically of rules, to enhance reusability across domains by separating procedural code and domain knowledge. A separate inference engine processes rules and adds, deletes, or modifies a knowledge store.


title: Symbolic artificial intelligence

text: Forward chaining inference engines are the most common, and are seen in CLIPS and OPS5. Backward chaining occurs in Prolog, where a more limited logical representation is used, Horn Clauses. Pattern-matching, specifically unification, is used in Prolog.


title: Symbolic artificial intelligence

text: A more flexible kind of problem-solving occurs when reasoning about what to do next occurs, rather than simply choosing one of the available actions. This kind of meta-level reasoning is used in Soar and in the BB1 blackboard architecture.


title: Symbolic artificial intelligence

text: Cognitive architectures such as ACT-R may have additional capabilities, such as the ability to compile frequently used knowledge into higher-level chunks.


title: Symbolic artificial intelligence

text: Marvin Minsky first proposed frames as a way of interpreting common visual situations, such as an office, and Roger Schank extended this idea to scripts for common routines, such as dining out. Cyc has attempted to capture useful common-sense knowledge and has "micro-theories" to handle particular kinds of domain-specific reasoning.


title: Symbolic artificial intelligence

text: Qualitative simulation, such as Benjamin Kuipers's QSIM, approximates human reasoning about naive physics, such as what happens when we heat a liquid in a pot on the stove. We expect it to heat and possibly boil over, even though we may not know its temperature, its boiling point, or other details, such as atmospheric pressure.


title: Symbolic artificial intelligence

text: Similarly, Allen's temporal interval algebra is a simplification of reasoning about time and Region Connection Calculus is a simplification of reasoning about spatial relationships. Both can be solved with constraint solvers.


title: Symbolic artificial intelligence

text: Constraint solvers perform a more limited kind of inference than first-order logic. They can simplify sets of spatiotemporal constraints, such as those for RCC or Temporal Algebra, along with solving other kinds of puzzle problems, such as Wordle, Sudoku, cryptarithmetic problems, and so on. Constraint logic programming can be used to solve scheduling problems, for example with constraint handling rules (CHR).


title: Symbolic artificial intelligence

text: The General Problem Solver (GPS) cast planning as problem-solving used means-ends analysis to create plans. STRIPS took a different approach, viewing planning as theorem proving. Graphplan takes a least-commitment approach to planning, rather than sequentially choosing actions from an initial state, working forwards, or a goal state if working backwards. Satplan is an approach to planning where a planning problem is reduced to a Boolean satisfiability problem.


title: Symbolic artificial intelligence

text: Natural language processing focuses on treating language as data to perform tasks such as identifying topics without necessarily understanding the intended meaning. Natural language understanding, in contrast, constructs a meaning representation and uses that for further processing, such as answering questions.


title: Symbolic artificial intelligence

text: Parsing, tokenizing, spelling correction, part-of-speech tagging, noun and verb phrase chunking are all aspects of natural language processing long handled by symbolic AI, but since improved by deep learning approaches. In symbolic AI, discourse representation theory and first-order logic have been used to represent sentence meanings. Latent semantic analysis (LSA) and explicit semantic analysis also provided vector representations of documents. In the latter case, vector components are interpretable as concepts named by Wikipedia articles.


title: Symbolic artificial intelligence

text: New deep learning approaches based on Transformer models have now eclipsed these earlier symbolic AI approaches and attained state-of-the-art performance in natural language "processing". However, Transformer models are opaque and do not yet produce human-interpretable semantic representations for sentences and documents. Instead, they produce task-specific vectors where the meaning of the vector components is opaque.


title: Symbolic artificial intelligence

text: Agents are autonomous systems embedded in an environment they perceive and act upon in some sense. Russell and Norvig's standard textbook on artificial intelligence is organized to reflect agent architectures of increasing sophistication. The sophistication of agents varies from simple reactive agents, to those with a model of the world and automated planning capabilities, possibly a BDI agent, i.e., one with beliefs, desires, and intentions – or alternatively a reinforcement learning model learned over time to choose actions – up to a combination of alternative architectures, such as a neuro-symbolic architecture that includes deep learning for perception.


title: Symbolic artificial intelligence

text: In contrast, a multi-agent system consists of multiple agents that communicate amongst themselves with some inter-agent communication language such as Knowledge Query and Manipulation Language (KQML). The agents need not all have the same internal architecture. Advantages of multi-agent systems include the ability to divide work among the agents and to increase fault tolerance when agents are lost. Research problems include how agents reach consensus, distributed problem solving, multi-agent learning, multi-agent planning, and distributed constraint optimization.


title: Symbolic artificial intelligence

text: Controversies arose from early on in symbolic AI, both within the field—e.g., between logicists (the pro-logic "neats") and non-logisists (the anti-logic "scruffies")—and between those who embraced AI but rejected symbolic approaches—primarily connectionists—and those outside the field. Critiques from outside of the field were primarily from philosophers, on intellectual grounds, but also from funding agencies, especially during the two AI winters.


title: Symbolic artificial intelligence

text: Connectionist approaches include earlier work on neural networks, such as perceptrons; work in the mid to late 80s, such as Danny Hillis's Connection Machine and Yann Le Cun's advances in convolutional neural networks; to today's more advanced approaches, such as Transformers, GANs, and other work in deep learning.


title: Symbolic artificial intelligence

text: Olazaran, in his sociological history of the controversies within the neural network community, described the moderate connectionism view as essentially compatible with current research in neuro-symbolic hybrids:


title: Symbolic artificial intelligence

text: The third and last position I would like to examine here is what I call the moderate connectionist view, a more eclectic view of the current debate between connectionism and symbolic AI. One of the researchers who has elaborated this position most explicitly is Andy Clark, a philosopher from the School of Cognitive and Computing Sciences of the University of Sussex (Brighton, England). Clark defended hybrid (partly symbolic, partly connectionist) systems. He claimed that (at least) two kinds of theories are needed in order to study and model cognition. On the one hand, for some information-processing tasks (such as pattern recognition) connectionism has advantages over symbolic models. But on the other hand, for other cognitive processes (such as serial, deductive reasoning, and generative symbol manipulation processes) the symbolic paradigm offers adequate models, and not only "approximations" (contrary to what radical connectionists would claim).


title: Symbolic artificial intelligence

text: Gary Marcus has claimed that the animus in the deep learning community against symbolic approaches now may be more sociological than philosophical:To think that we can simply abandon symbol-manipulation is to suspend disbelief.


title: Symbolic artificial intelligence

text: And yet, for the most part, that's how most current AI proceeds. Hinton and many others have tried hard to banish symbols altogether. The deep learning hope—seemingly grounded not so much in science, but in a sort of historical grudge—is that intelligent behavior will emerge purely from the confluence of massive data and deep learning. Where classical computers and software solve tasks by defining sets of symbol-manipulating rules dedicated to particular jobs, such as editing a line in a word processor or performing a calculation in a spreadsheet, neural networks typically try to solve tasks by statistical approximation and learning from examples.According to Marcus, Geoffrey Hinton and his colleagues have been vehemently "anti-symbolic":When deep learning reemerged in 2012, it was with a kind of take-no-prisoners attitude that has characterized most of the last decade. By 2015, his hostility toward all things symbols had fully crystallized. He gave a talk at an AI workshop at Stanford comparing symbols to aether, one of science's greatest mistakes.


title: Symbolic artificial intelligence

text: Since then, his anti-symbolic campaign has only increased in intensity. In 2016, Yann LeCun, Bengio, and Hinton wrote a manifesto for deep learning in one of science's most important journals, Nature. It closed with a direct attack on symbol manipulation, calling not for reconciliation but for outright replacement. Later, Hinton told a gathering of European Union leaders that investing any further money in symbol-manipulating approaches was "a huge mistake," likening it to investing in internal combustion engines in the era of electric cars.


title: Symbolic artificial intelligence

text: Turing award winner Judea Pearl offers a critique of machine learning which, unfortunately, conflates the terms machine learning and deep learning. Similarly, when Geoffrey Hinton refers to symbolic AI, the connotation of the term tends to be that of expert systems dispossessed of any ability to learn. The use of the terminology is in need of clarification. Machine learning is not confined to association rule mining, c.f. the body of work on symbolic ML and relational learning (the differences to deep learning being the choice of representation, localist logical rather than distributed, and the non-use of gradient-based learning algorithms). Equally, symbolic AI is not just about production rules written by hand. A proper definition of AI concerns knowledge representation and reasoning, autonomous multi-agent systems, planning and argumentation, as well as learning.


title: Symbolic artificial intelligence

text: Now we turn to attacks from outside the field specifically by philosophers. One argument frequently cited by philosophers was made earlier by the computer scientist Alan Turing, in his 1950 paper Computing Machinery and Intelligence, when he said that "human behavior is far too complex to be captured by any formal set of rules—humans must be using some informal guidelines that … could never be captured in a formal set of rules and thus could never be codified in a computer program." Turing called this "The Argument from Informality of Behaviour."


title: Symbolic artificial intelligence

text: Similar critiques were provided by Hubert Dreyfus, in his books "What Computers Can't Do" and "What Computers Still Can't Do". Dreyfus predicted AI would only be suitable for toy problems, and thought that building more complex systems or scaling up the idea towards useful software would not be possible. John Haugeland, another philosopher, similarly argued against rule-based symbolic AI in his book "Artificial Intelligence: The Very Idea", calling it GOFAI ("Good Old-Fashioned Artificial Intelligence").


title: Symbolic artificial intelligence

text: Russell and Norvig explain that these arguments were targeted to the symbolic AI of the 1980s:The technology they criticized came to be called Good Old-Fashioned AI (GOFAI). GOFAI corresponds to the simplest logical agent design described ... and we saw ... that it is indeed difficult to capture every contingency of appropriate behavior in a set of necessary and sufficient logical rules; we called that the qualification problem.


title: Symbolic artificial intelligence

text: Since then, probabilistic reasoning systems have extended the capability of symbolic AI so they can be much "more appropriate for open-ended domains." However, Dreyfus raised another argument that cannot be addressed by disembodied symbolic AI systems:


title: Symbolic artificial intelligence

text: One of Dreyfus's strongest arguments is for situated agents rather than disembodied logical inference engines. An agent whose understanding of "dog" comes only from a limited set of logical sentences such as "Dog(x) ⇒ Mammal(x)" is at a disadvantage compared to an agent that has watched dogs run, has played fetch with them, and has been licked by one. As philosopher Andy Clark (1998) says, "Biological brains are first and foremost the control systems for biological bodies. Biological bodies move and act in rich real-world surroundings." According to Clark, we are "good at frisbee, bad at logic."


title: Symbolic artificial intelligence

text: The embodied cognition approach claims that it makes no sense to consider the brain separately: cognition takes place within a body, which is embedded in an environment. We need to study the system as a whole; the brain's functioning exploits regularities in its environment, including the rest of its body. Under the embodied cognition approach, robotics, vision, and other sensors become central, not peripheral.


title: Symbolic artificial intelligence

text: Rodney Brooks, created behavior-based robotics, also named Nouvelle AI, as an alternative to "both" symbolic AI and connectionist AI. His approach rejected representations, either symbolic or distributed, as not only unnecessary, but as detrimental. Instead, he created the subsumption architecture, a layered architecture for embodied agents. Each layer achieves a different purpose and must function in the real world. For example, the first robot he describes in "Intelligence Without Representation", has three layers. The bottom layer interprets sonar sensors to avoid objects. The middle layer causes the robot to wander around when there are no obstacles. The top layer causes the robot to go to more distant places for further exploration. Each layer can temporarily inhibit or suppress a lower-level layer. He criticized AI researchers for defining AI problems for their systems, when: "There is no clean division between perception (abstraction) and reasoning in the real world." He called his robots "Creatures" and each layer was "composed of a fixed-topology network of simple finite state machines." In the Nouvelle AI approach, "First, it is vitally important to test the Creatures we build in the real world; i.e., in the same world that we humans inhabit. It is disastrous to fall into the temptation of testing them in a simplified world first, even with the best intentions of later transferring activity to an unsimplified world." His emphasis on real-world testing was in contrast to "Early work in AI concentrated on games, geometrical problems, symbolic algebra, theorem proving, and other formal systems" and the use of the blocks world in symbolic AI systems such as SHRDLU.


title: Symbolic artificial intelligence

text: Each approach—symbolic, connectionist, and behavior-based—has advantages, but has been criticized by the other approaches. Symbolic AI has been criticized as disembodied, liable to the qualification problem, and poor in handling the perceptual problems where deep learning excels. In turn, connectionist AI has been criticized as poorly suited for deliberative step-by-step problem solving, incorporating knowledge, and handling planning. Finally, Nouvelle AI excels in reactive and real-world robotics domains but has been criticized for difficulties in incorporating learning and knowledge.


title: Symbolic artificial intelligence

text: Hybrid AIs incorporating one or more of these approaches are currently viewed as the path forward. Russell and Norvig conclude that:Overall, Dreyfus saw areas where AI did not have complete answers and said that Al is therefore impossible; we now see many of these same areas undergoing continued research and development leading to increased capability, not impossibility.


title: Kim Jun-ho (comedian)

text: Kim Jun-ho (born December 25, 1975), also known as Charlie Kim, is a South Korean comedian, singer and television personality. He has starred in "Gag Concert" since 1999 and was a member of the variety show "2 Days & 1 Night" from 2013 to 2019. He has also been the executive chairman of Busan International Comedy Festival since its conception in 2013.


title: Kim Jun-ho (comedian)

text: Considered one of the best comedians in South Korea, Kim has won two Top Excellence awards and a Daesang Award at the KBS Entertainment Awards in both comedy and variety divisions.


title: Kim Jun-ho (comedian)

text: Kim was born in Daejeon, South Korea. His sister, Kim Mi-jin, is a TV show host He graduated from Chungnam High School and was majoring in acting at Dankook University before dropping out.


title: Kim Jun-ho (comedian)

text: Kim is greatly influenced by the famous comedian, Charlie Chaplin. For this reason he chose "Charlie Kim" as his English name.


title: Kim Jun-ho (comedian)

text: On March 2, 2006, Kim married musical actress Kim Eun-young. The couple lived separately since 2007 after Kim Eun-young moved to the Philippines alone to start a business. On January 22, 2018, the comedian announced his divorce with his wife after 12 years of marriage.


title: Kim Jun-ho (comedian)

text: Kim originally debuted under SBS's 5th class of comedians. He later joined KBS's "Gag Concert" in 1999 and is part of its 14th class. He was also a cast member for the first season of "The Human Condition""." He joined the "2 Days & 1 Night" Season 3 lineup with Kim Joohyuk, Defconn and Jung Joon Young at the very end of 2013, gaining popularity as well as earning the nickname of "Mr. Devious" for his tendency to trick the other cast members. Kim is the chairman and head of the organizing committee for the Busan International Comedy Festival. He is a member of 같기도 (Gatgido), a comedic trio, which released an album with the same name in 2007.


title: Kim Jun-ho (comedian)

text: Kim was the co-CEO and founder of CoKo Entertainment. However, in late 2014, it was discovered that his partner and co-CEO, Kim Woo Jung, had embezzled money from the company and had run away to the United States, causing the company debts to reach over millions of dollars. When it shut down from bankruptcy in January 2015, he and former comedians under CoKo company transferred to JD Bros, a company that is run by his friend, Kim Dae Hui. The comedians also cited that they will continue to support Kim Junho despite the incident.


title: Things Fall Apart (album)

text: Things Fall Apart is the fourth studio album by American hip hop band The Roots, released on February 23, 1999 by MCA Records. Recording sessions for the album took place at Electric Lady Studios during 1997 to 1998, coinciding with recording for other projects of the Soulquarians collective, including D'Angelo's "Voodoo" (2000), Erykah Badu's "Mama's Gun" (2000), and Common's "Like Water for Chocolate" (2000). According to "Spin" magazine, the album became a landmark moment for The Roots and the collective, as it "swelled the Roots clique into a movement-style posse".


title: Things Fall Apart (album)

text: The album has been considered by music writers as The Roots' breakthrough album, earning praise from major publications and critics, while becoming the group's first record to sell over 500,000 copies. It includes the song "You Got Me", which won the 2000 Grammy Award for Best Rap Performance by a Duo or Group, while "Things Fall Apart" was also nominated for the Grammy Award for Best Rap Album of the same year, losing to Eminem for "The Slim Shady LP". "Rolling Stone" called it a "top-flight record", while AllMusic cited it as "one of the cornerstone albums of alternative rap." The album takes its title from Chinua Achebe's novel of the same name, which in turn took the phrase from William Butler Yeats's poem "The Second Coming". On April 5, 1999, "Things Fall Apart" was certified Gold by the Recording Industry Association of America (RIAA) for shipments of 500,000 units and on April 22, 2013, fourteen years after its release, the album was certified Platinum by RIAA for shipments of 1,000,000 units.


title: Things Fall Apart (album)

text: Recording for "Things Fall Apart" began in 1997 and was completed in early 1998. Sessions for the album coincided with those for other Soulquarians projects at Electric Lady Studios, including D'Angelo's "Voodoo" (2000), Erykah Badu's "Mama's Gun" (2000), and Common's "Like Water for Chocolate" (2000). Questlove has stated that during this period, the group recorded upwards of around 145 songs, later whittling down their choices to 14 songs (intros and interludes withstanding). The last song to be included to the final selection was "Double Trouble", featuring Mos Def. Initially, the song was supposed to feature a guest appearance from Mos' Black Star partner, Talib Kweli but due to the format of the track, it was decided to make it a throwback to the Run D.M.C./EPMD tag-team style of rap, with just two MCs.


title: Things Fall Apart (album)

text: The album's opening track, "Act Won", contains an excerpt from the Spike Lee film, "Mo' Better Blues". The excerpt comes from a scene where Denzel Washington and Wesley Snipes are discussing the current state of African American music (or culture in general) after a gig. The track "Act Too (The Love of My Life)", originally an interlude that evolved into a full song, features Common, whose verse is a continuation of his song "I Used to Love H.E.R.", off his 1994 album "Resurrection", in which Common speaks of hip hop as a woman. However, Questlove has stated that this is not "I used to love H.E.R. (the daughter), rather it is a "reflection on the evolution of hip hop, through our eyes." Beanie Sigel made his recording debut on the track "Adrenaline!", after tagging along to a weekly jam session held by the group in Philadelphia. Eve (at the time, signed to Dr. Dre's Aftermath label, and known as Eve of Destruction) also made her debut on "Things Fall Apart", on the track, "You Got Me".


title: Things Fall Apart (album)

text: "You Got Me" was co-written by Jill Scott who recorded vocals for the song's chorus and bridge. Scott's part was subsequently re-recorded by Erykah Badu at the insistence of MCA, who wanted a higher profile collaboration for the album's official lead single – as Scott was relatively unknown outside of Philadelphia at the time. When the group later went on tour, Scott joined them during performances of the song. "You Got Me" caught on quickly on the radio and later MTV, giving the group a much needed boost in terms of sales and exposure. Its Grammy win provided a second round of success. The outside musicians who contributed to the album (mainly D'Angelo, James Poyser, and Jay Dee) were part of the Soulquarians collective with Questlove and Pino Palladino.


title: Things Fall Apart (album)

text: Upon its release, "Things Fall Apart" was widely regarded as the group's most fully realized work. Critics praised the album for its sobering themes, sonic quality, and fluid, cohesive sequencing, with Touré of "Rolling Stone" calling it a "top-flight record" and lead MC Black Thought a "lyricist's lyricist with a hard, earnest voice that doesn't flow like water but bobs and weaves with less-predictable rhythms". "Mojo" commented that the album is "the stunner they've always promised: the first candidate for hip hop album of 1999 ... in a hip-hop world dominated by well-worn pop samples and rap rewrites of 80's chart hits, such risk-taking should be cherished". Marie Elsie St. Léger of Barnes & Noble wrote in her review that the album had "Unfussy yet precise production, irresistible beats, and smooth rhymes. Few albums manage to simultaneously be this informative, political, and downright groovy." "Spin"s Neil Kulkarni suggested that "the Roots have created perhaps rap's first melancholy masterpiece", noting "a downered, fragmented feel to the music that weaves through the lyrics' bleak resignation to instill real poignancy and effect."


title: Things Fall Apart (album)

text: Steve Jones of "USA Today" complimented the band's "jazzy, live instrumentation and dense, insightful lyrics" and commented that it "elevates hip-hop with literate, thoughtful grooves". In his consumer guide for "The Village Voice", Robert Christgau criticized Kamal Gray's "omnipresent ostinato beds", but commended the band for "looking back to the old-school rap they loved before they discovered jazz lite", and stated "What's so consistently annoying on their earlier intelligent records is almost hooky on this one, integral to a flow that certainly does just that, which isn't to say you won't be relieved when it rocks the house instead". Fans responded with as much enthusiasm, and the album shipped Platinum in the United States.


title: Things Fall Apart (album)

text: AllMusic critic Steve Huey hailed "Things Fall Apart" as "one of the cornerstone albums of alternative rap", believing that it was "the point where the Roots' tremendous potential finally coalesced into a structured album that maintained its focus from top to bottom". Writing for "The Root" in 2018, Panama Jackson described "Act Too (The Love of My Life)" as "one of the best beats in hip-hop history...it's so ethereal and beautiful and fit perfectly with the verses". In 2020, the album was ranked number 416 on "Rolling Stone"s list of the 500 Greatest Albums of All Time.


title: Things Fall Apart (album)

text: For a limited time period, "Things Fall Apart" was made available with a choice of five different front covers. One such cover displays a photograph taken during a riot in the civil rights movement era. In the stark black-and-white photo, riot police are seen chasing two black teenagers on the streets of Bedford-Stuyvesant. In 2005, this cover was included in the book, "The Greatest Album Covers Of All Time" by Barry Miles, Grant Scott & Johnny Morgan, and published by Collins & Brown.


title: Ashley Hinson

text: Ashley Elizabeth Hinson (born June 27, 1983) is an American politician and journalist serving as the U.S. representative for Iowa's 1st congressional district since 2021. Her district comprises much of the northeast quadrant of the state, including Cedar Rapids, Waterloo, Cedar Falls, and Dubuque.


title: Ashley Hinson

text: A member of the Republican Party, Hinson was the Iowa State Representative for the 67th district from 2017 to 2021, the first woman to represent the district. She won a seat in the United States House of Representatives in the 2020 election, narrowly defeating incumbent Democrat Abby Finkenauer. Hinson and Mariannette Miller-Meeks are the first Republican women to represent Iowa in the House.


title: Ashley Hinson

text: A native of Des Moines, Iowa, Hinson is a graduate of Valley High School in West Des Moines and the University of Southern California, where she studied broadcast journalism. She is an alumna of the Pi Beta Phi sorority. Hinson began her career as an anchor for KCRG-TV.


title: Ashley Hinson

text: In 2016, Hinson ran for Iowa's 67th House District, based in Linn County, Iowa. She defeated Democrat Mark Seidl, 62.5%-37.5%.


title: Ashley Hinson

text: This Cedar Rapids suburban district is very competitive. 2016 Democratic presidential nominee Hillary Clinton won it over Donald Trump by two percentage points.


title: Ashley Hinson

text: In the Iowa House, Hinson served on the Judiciary committee, the Public Safety committee, and the Transportation committee, which she chaired. She also served on the Transportation, Infrastructure, and Capitals Appropriations Subcommittee.


title: Ashley Hinson

text: On May 13, 2019, Hinson filed paperwork to run against Democratic incumbent Abby Finkenauer in Iowa's 1st congressional district.


title: Ashley Hinson

text: The district, which encompasses 20 counties in northeastern Iowa, was flipped in the 2018 election. Hinson was announced as a "contender" by the National Republican Congressional Committee. She was endorsed by Iowa Governor Kim Reynolds and Lieutenant Governor Adam Gregg. On June 2, 2020, Hinson won the Republican primary.


title: Ashley Hinson

text: Hinson focused her campaign on cutting taxes and building infrastructure. In July 2020, "The New York Times" reported several instances of Hinson's campaign website plagiarizing portions of articles from media outlets. Hinson said she "was unaware of the plagiarism when I reviewed drafts presented to me by staff. As a journalist I take this extremely seriously and am deeply sorry for the mistake. The staff responsible will be held accountable."


title: Ashley Hinson

text: On October 29, 2021, most of Hinson's territory, including her home in Marion, near Cedar Rapids, became the 2nd district due to redistricting, and Hinson announced she would seek reelection there. In effect, she traded district numbers with fellow freshman Republican Mariannette Miller-Meeks. Hinson defeated Democratic nominee Liz Mathis in the general election.


title: Ashley Hinson

text: Hinson, along with all other Senate and House Republicans, voted against the American Rescue Plan Act of 2021.


title: Ashley Hinson

text: On July 19, 2022, Hinson and 46 other Republican Representatives voted for the Respect for Marriage Act, which would codify the right to same-sex marriage in federal law.


title: Ashley Hinson

text: In 2022, Hinson was one of 39 Republicans to vote for the Merger Filing Fee Modernization Act of 2022, an antitrust package that would crack down on corporations for anti-competitive behavior.


title: NixOS

text: NixOS is a Linux distribution built on top of the Nix package manager. It uses declarative configuration and allows reliable system upgrades. Several official package "channels" are offered, including the current Stable release and the Unstable release which follows the latest development. NixOS has tools dedicated to DevOps and deployment tasks.


title: NixOS

text: In 2003, Eelco Dolstra started NixOS as a research project. In 2015, the Stichting NixOS was founded aiming to support projects like NixOS that implement the purely functional deployment model.


title: NixOS

text: NixOS publishes releases on a twice a year schedule. This used to happen around March and September but, starting with 21.05, NixOS targets May and November instead. Each version number has the format "YY.MM", for instance "20.03" was the version released in March 2020. Each version of NixOS has a name, such as "Markhor" for the release 20.03.


title: NixOS

text: In NixOS, the entire operating system – the kernel, applications, system packages, configuration files, and so on – is built by the Nix package manager from a description in a functional build language. This means that building a new configuration cannot overwrite previous configurations.


title: NixOS

text: A NixOS system is configured by writing a specification of the functionality that the user wants on their machine in a global configuration file. For instance, here is a minimal configuration of a machine running an SSH daemon:


title: NixOS

text: After changing the configuration file, the system can be updated using the codice_1 command. This command does everything necessary to apply the new configuration, including downloading and compiling packages and generating configuration files.


title: NixOS

text: Since Nix files are pure and declarative, evaluating them will always produce the same result, regardless of what packages or configuration files are on the system. Thus, upgrading a system is as reliable as reinstalling from scratch.


title: NixOS

text: NixOS has a transactional approach to configuration management making configuration changes such as upgrades atomic. This means that if the upgrade to a new configuration is interrupted – say, the power fails half-way through – the system will still be in a consistent state: it will either boot in the old or the new configuration. In other systems, a machine might end up in an inconsistent state, and may not even boot anymore.


title: NixOS

text: If after a system update the new configuration is undesirable, it can be rolled back using a special command (codice_2). Every system configuration version automatically shows up at the system boot menu. If the new configuration crashes or does not boot properly, an older version can be selected. Rollbacks are lightweight operations that do not involve files being restored from copies.


title: NixOS

text: NixOS's declarative configuration model makes it easy to reproduce a system configuration on another machine. Copying the configuration file to the target machine and running the system update command generates the same system configuration (kernel, applications, system services, and so on) except for parts of the system not managed by the package manager such as user data.


title: NixOS

text: The Nix build language used by NixOS specifies how to build packages from source. This makes it easy to adapt the system to user needs. However, building from source being a slow process, the package manager automatically downloads pre-built binaries from a cache server when they are available. This gives the flexibility of a source-based package management model with the efficiency of a binary model.


title: NixOS

text: The Nix package manager ensures that the running system is consistent with the logical specification of the system, meaning that it will rebuild all packages that need to be rebuilt. For instance, if the kernel is changed then the package manager will ensure that external kernel modules will be rebuilt. Similarly, when a library is updated it ensures that all the system packages use the new version, even packages statically linked to it.


title: NixOS

text: There is no need for special privileges to install software in NixOS. In addition to the system-wide profile, every user has a dedicated profile in which they can install packages. Nix also allows multiple versions of a package to coexist, so different users can have different versions of the same package installed in their respective profiles. If two users install the same version of a package, only one copy will be built or downloaded. Nix's security model ensures that this is secure because only the users explicitly trusted by the system configuration are allowed to use build parameters that would allow them to control the content of a derivation's output (such as adding impurities to the sandbox or using an untrusted substituter). Without those parameters, paths can only be substituted from a substituter trusted by the system or a local sandboxed build which is implicitly trusted.


title: NixOS

text: NixOS is based on the Nix package manager that stores all packages in isolation from each other in the package store.


title: NixOS

text: Installed packages are identified by a cryptographic hash of all input used for their build. Changing the build instructions of a package modifies its hash and that will result in a different package installed in the package store. This system is also used to manage configuration files ensuring that newer configurations are not overwriting older ones.


title: NixOS

text: An implication of this is that NixOS doesn't follow the Filesystem Hierarchy Standard. The only exceptions are a symlink /bin/sh to the version of bash in the Nix store (like this: codice_3); and while NixOS does have an /etc directory to keep system-wide configuration files, most files in that directory are symlinks to generated files in /nix/store such as codice_4. Not using global directories such as /bin is part of what allows multiple versions of a package to coexist.


title: The Gorge Amphitheatre

text: The Gorge Amphitheatre, originally known as Champs de Brionne Music Theatre, is an outdoor concert venue in Grant County, Washington, United States. It is situated near Columbia River in Central Washington, west of George. The venue is managed by Live Nation.


title: The Gorge Amphitheatre

text: It is a nine-time winner of "Pollstar" Magazine's award for 'Best Outdoor Music Venue' and was voted as one of the 'Best Outdoor Concert Venues in America' by ConcertBoom.


title: The Gorge Amphitheatre

text: The original amphitheater was owned and operated by Dr. Vincent Bryan and Carol Bryan, along with the adjoining winery, Champs de Brionne, for which it was named. It opened in 1986 and seated 3,000 people, but had expanded to 19,000 prior to the purchase by MCA in 1993. The Gorge Amphitheater was acquired by Live Nation in 2006.


title: The Gorge Amphitheatre

text: North of Interstate 90, The Gorge is approximately east of Seattle and approximately west of Spokane. This venue offers views of the Columbia River, Columbia Gorge canyon, eastern Kittitas, and western Grant County. Originally, the land was planned to be used for growing grapes for wine.


title: The Gorge Amphitheatre

text: Apart from drawing big name performers, The Gorge has also played host to an array of popular music festivals, including Area Festival, Creation Festival, Dave Matthews Band Caravan, H.O.R.D.E. Festival, Honda Civic Tour, Identity Festival, Lilith Fair, Lollapalooza, Ozzfest, Paradiso Festival, Rock the Bells Festival, Sasquatch! Music Festival, Uproar Festival, Vans Warped Tour, Pain in the Grass, and Watershed Festival as well as Phish, who has played 22 times since 1997.


title: The Gorge Amphitheatre

text: The White River Amphitheatre opened in 2003, directly competing with the venue. The new amphitheater is substantially closer to Seattle, with a shorter travel time via car of 1.5 to 2.25 hours less, depending on traffic. A columnist for "The Seattle Times" noted the preferable view and "experience" offered by The Gorge.


title: The Gorge Amphitheatre

text: As of 2022, Dave Matthews Band has played 70 shows at the venue, traditionally during their Labor Day weekend three-night run. "The Gorge", a combination 2-CD/1-DVD set with highlights from their 3-night 2002 tour closer here was released on June 29, 2004. Additionally, their September 4, 2016 tour closer was released as Live Trax, Vol. 44 on December 8, 2017.


title: The Gorge Amphitheatre

text: Pearl Jam (from Seattle) released a box set, featuring their entire performances from 2005 and 2006, aptly titled, "Live at the Gorge 05/06."


title: The Gorge Amphitheatre

text: About 400,000 people attended concerts at The Gorge Amphitheater in the year 2013. Above and Beyond hosted their 250th episode of "Group Therapy Radio" at The Gorge on September 16, 2017 to September 17, 2017.


title: The Gorge Amphitheatre

text: A documentary film titled ""Enormous: The Gorge Story"" was released in 2021. The film focused on The Gorge and its music history.


title: The Gorge Amphitheatre

text: Excision began hosting his weekend-long electronic music festival Bass Canyon here in August 2018. The second year of the festival took place on August 23–25, 2019 and featured artists such as Excision himself, Flux Pavilion, Zomboy, Wooli, Virtual Riot, Subtronics, Liquid Stranger, and many more.


title: The Gorge Amphitheatre

text: Fans can stay in the campground for 24 hours on the day of a single show, or until 12 noon the day after a run of shows end. Camping at the Gorge requires buying a camping ticket, which can be included in the concert admission ticket.


title: The Gorge Amphitheatre

text: The campground at the Gorge sets aside spaces for one car with up to two two-person tents or a single RV. There are very limited RV hookups at the Gorge campground. Sites are set aside by venue staff on a first-come, first-served basis. Potable water, flush toilets, hot showers, and a convenience store are available on the grounds. The campground also has 24-hour security.


title: John Jellicoe, 1st Earl Jellicoe

text: Admiral of the Fleet John Rushworth Jellicoe, 1st Earl Jellicoe, (5 December 1859 – 20 November 1935) was a Royal Navy officer. He fought in the Anglo-Egyptian War and the Boxer Rebellion and commanded the Grand Fleet at the Battle of Jutland in May 1916 during the First World War. His handling of the fleet at that battle was controversial. Jellicoe made no serious mistakes and the German High Seas Fleet retreated to port, at a time when defeat would have been catastrophic for Britain, but the public was disappointed that the Royal Navy had not won a more dramatic victory given that they outnumbered the enemy. Jellicoe later served as First Sea Lord, overseeing the expansion of the Naval Staff at the Admiralty and the introduction of convoys, but was relieved at the end of 1917. He also served as the Governor-General of New Zealand in the early 1920s.


title: John Jellicoe, 1st Earl Jellicoe

text: Jellicoe was born on 5 December 1859 in Southampton, Hampshire. Jellicoe was the son of John Henry Jellicoe, a captain in the Royal Mail Steam Packet Company, and Lucy Henrietta Jellicoe (née Keele). He was educated at Field House School in Rottingdean and aboard the training ship , which he joined as a naval cadet in 1872. He was made a midshipman in the steam frigate in September 1874 before transferring to the ironclad in the Mediterranean Fleet in July 1877. Promoted to sub-lieutenant on 5 December 1878, he joined , flagship of the Mediterranean Fleet, as signal sub-lieutenant in 1880. Promoted to lieutenant on 23 September 1880, he returned to HMS "Agincourt" in February 1881 and commanded a rifle company of the Naval Brigade at Ismailia during the Egyptian war of 1882.


title: John Jellicoe, 1st Earl Jellicoe

text: Jellicoe qualified as a gunnery officer in 1883 and was appointed to the staff of the gunnery school in May 1884. He joined the turret ship as gunnery officer in September 1885 and was awarded the Board of Trade Silver Medal for rescuing the crew of a capsized steamer near Gibraltar in May 1886. He joined the battleship in April 1886 and was put in charge of the experimental department at HMS "Excellent" in December 1886 before being appointed an assistant to the Director of Naval Ordnance in September 1889.


title: John Jellicoe, 1st Earl Jellicoe

text: Promoted to commander on 30 June 1891, Jellicoe joined the battleship in the Mediterranean Fleet in March 1892. He transferred to the battleship in 1893 (the flagship of the Commander-in-Chief of the Mediterranean Fleet, Vice Admiral Sir George Tryon) and was aboard when it collided with and sank off Tripoli in Lebanon on 22 June 1893. He was then appointed to the new flagship, , in October 1893.


title: John Jellicoe, 1st Earl Jellicoe

text: Promoted to captain on 1 January 1897, Jellicoe became a member of the Admiralty's Ordnance Committee. He served as Captain of the battleship and chief of staff to Vice Admiral Sir Edward Seymour during the Seymour Expedition to relieve the legations at Peking during the Boxer Rebellion in June 1900. He was badly wounded during the Battle of Beicang and told he would die but confounded the attending doctor and chaplain by living. He was appointed a Companion of the Order of the Bath and given the German Order of the Red Eagle, 2nd class, with Crossed Swords for services rendered in China. "Centurion" returned to the United Kingdom in August 1901, and was paid off the following month, when Captain Jellicoe and the crew went on leave. He became Naval Assistant to Third Naval Lord and Controller of the Navy in February 1902 and was given command of the armoured cruiser on the North America and West Indies Station in August 1903.


title: John Jellicoe, 1st Earl Jellicoe

text: As a protege of Admiral John Fisher, Jellicoe became Director of Naval Ordnance in 1905 and, having been appointed a Commander of the Royal Victorian Order on the occasion of launching of on 10 February 1906, he was also made an Aide-de-Camp to the King on 8 March 1906. Promoted to rear admiral on 8 February 1907, he pushed hard for funds to modernise the navy, supporting the construction of new -type battleships and s. He supported F. C. Dreyer's improvements in gunnery fire-control systems, and favoured the adoption of Dreyer's "Fire Control Table", a form of mechanical computer for calculating firing solutions for warships. Jellicoe arranged for the output of naval ordnance to be transferred from the War Office to the Admiralty.


title: John Jellicoe, 1st Earl Jellicoe

text: Jellicoe was appointed second-in-command of the Atlantic Fleet in August 1907, hoisting his flag in the battleship . He was appointed Knight Commander of the Royal Victorian Order on the occasion of the King's Review of the Home Fleet in the Solent on 3 August 1907. He went on to be Third Sea Lord and Controller of the Navy in October 1908 and, having taken part in the funeral of King Edward VII in May 1910, he became Commander-in-Chief, Atlantic Fleet in December 1910, hoisting his flag in the battleship . He advanced to Knight Commander of the Order of the Bath on the Coronation of King George V on 19 June 1911 and confirmed in the rank of vice admiral on 18 September 1911. He went on to be Second-in-Command of the Home Fleet, hoisting his flag in the battleship , in December 1911 and, having also been appointed commander of the 2nd Battle Squadron in May 1912, joined the Royal Commission on Fuel and Engines on 1 August 1912. He became Second Sea Lord in December 1912.


title: John Jellicoe, 1st Earl Jellicoe

text: At the start of the First World War, the First Lord of the Admiralty Winston Churchill, removed Admiral George Callaghan, Commander-in-Chief of the Home Fleet (August 1914). Jellicoe was promoted to full admiral on 4 August 1914 and assigned command of the renamed Grand Fleet in Admiral Callaghan's place, though he was appalled by the treatment of his predecessor. He was advanced to Knight Grand Cross of the Order of the Bath on 8 February 1915.


title: John Jellicoe, 1st Earl Jellicoe

text: When Fisher (First Sea Lord) and Churchill (First Lord of the Admiralty) both had to leave office (May 1915) after their quarrel over the Dardanelles, Jellicoe wrote to Fisher: "We owe you a debt of gratitude for having saved the Navy from a continuance in office of Mr Churchill, and I hope that never again will any politician be allowed to usurp the functions that he took upon himself to exercise".


title: John Jellicoe, 1st Earl Jellicoe

text: Jellicoe commanded the British Grand Fleet at the Battle of Jutland in May 1916, the largest (and only major) clash of dreadnoughts, albeit an indecisive one. His handling of the Grand Fleet during the battle remains controversial, with some historians characterising Jellicoe as too cautious and other historians faulting the battlecruiser commander, Admiral David Beatty, for making various tactical errors. Jellicoe certainly made no significant mistakes during the battle: based on limited intelligence, he correctly deployed the Grand Fleet with a turn to port so as to "cross the T" of the German High Seas Fleet as it appeared. After suffering heavy damage from shells, the German fleet turned 180 degrees and headed away from the battle. At the time the British public expressed disappointment that the Royal Navy had not won a victory on the scale of the 1805 Battle of Trafalgar. Churchill described Jellicoe later as "the only man on either side who could lose the war in an afternoon"—essentially hinting that Jellicoe's decision to prefer caution was strategically correct. He was appointed a member of the Order of Merit on 31 May 1916, advanced to Knight Grand Cross of the Royal Victorian Order on 17 June 1916 and awarded the Grand Cross of the French Legion of Honour on 15 September 1916.


title: John Jellicoe, 1st Earl Jellicoe

text: Jellicoe was appointed First Sea Lord in November 1916. His term of office saw Britain brought within danger of starvation by German unrestricted U-Boat warfare.


title: John Jellicoe, 1st Earl Jellicoe

text: At the War Committee (a Cabinet Committee which discussed strategy in 1915–16) in November 1916, the admirals present, including Jellicoe, told Lloyd George that convoys presented too large a target for enemy ships, and that merchant ship masters lacked the discipline to "keep station" in a convoy. In February 1917, Maurice Hankey wrote a memorandum for Lloyd George calling for the introduction of "scientifically organised convoys", almost certainly after being persuaded by Commander Henderson and the Shipping Ministry officials with whom he was in contact. After a breakfast meeting (13 February 1917) with Lloyd George, Carson (First Lord of the Admiralty) and Admirals Jellicoe and Duff agreed to "conduct experiments". However, convoys were not in general use until August 1917, by which time shipping losses to U-boats were already falling from their April peak.


title: John Jellicoe, 1st Earl Jellicoe

text: Jellicoe continued to take a pessimistic view, advising the War Policy Committee (a Cabinet Committee which discussed strategy in 1917) during planning meetings for the Third Ypres Offensive in June and July that nothing could be done to defeat the U-boats. However, removing Jellicoe in July, as Lloyd George wanted, would have been politically impossible given Conservative anger at the return of Churchill (still blamed for the Dardanelles) to office as Minister of Munitions. In August and September Lloyd George was preoccupied with Third Ypres and the possible transfer of resources to Italy, whilst the new First Lord of the Admiralty, Sir Eric Campbell Geddes, was reforming the Naval Staff (including creating a post for Wemyss as Deputy First Sea Lord). Geddes and Lloyd George met with Balfour and Carson (both former First Lords of the Admiralty) on 26 October to discuss sacking Jellicoe after he had failed to act on "secret, but absolutely reliable" information about a German attack on a Norwegian convoy, but again nothing came of this as Lloyd George was soon preoccupied by the Battle of Caporetto and the setting up of the Supreme War Council. Geddes wanted to return to his previous job in charge of military transportation in France, and by December it was clear that Lloyd George would have to sack Jellicoe or lose Geddes.


title: John Jellicoe, 1st Earl Jellicoe

text: Jellicoe was rather abruptly dismissed by Geddes in December 1917. Before he left for leave on Christmas Eve he received a letter from Geddes demanding his resignation. Geddes' letter stated that he was still in the building and available to talk, but after consulting Admiral Halsey Jellicoe replied in writing that he would "do what was best for the service". The move became public knowledge two days later.


title: John Jellicoe, 1st Earl Jellicoe

text: The Christmas holiday, when Parliament was not sitting, provided a good opportunity to remove Jellicoe with a minimum of fuss. Geddes squared matters with the King and with the Grand Fleet commander Admiral Beatty (who had initially written to Jellicoe of his "dismay" over his sacking and promised to speak to Geddes, but then did not write to him again for a month) over the holiday. The other Sea Lords talked of resigning (although Jellicoe advised them not to do so), especially when Geddes suggested in a meeting (31 December) that Balfour and Carson had specifically recommended Jellicoe's removal at the 26 October meeting; they had not done so, although Balfour's denial was less than emphatic. There was no trouble from the generals, who had a low opinion of Jellicoe. In the end the Sea Lords remained in place, whilst Carson remained a member of the War Cabinet, resigning in January over Irish Home Rule.


title: John Jellicoe, 1st Earl Jellicoe

text: Although it was pretended that the decision had been Geddes' alone, he let slip in the Naval Estimates debate (6 March 1918) that he had been conveying "the decision of the Government", i.e. of Lloyd George, who had never put the matter to the War Cabinet. MPs picked up on his slip immediately, and Bonar Law (Conservative Leader) admitted in the same debate that he too had had prior knowledge.


title: John Jellicoe, 1st Earl Jellicoe

text: As First Sea Lord Jellicoe was awarded the Grand Cordon of the Belgian Order of Leopold on 21 April 1917, the Russian Order of St. George, 3rd Class on 5 June 1917, the Grand Cross of the Italian Military Order of Savoy on 11 August 1917 and the Grand Cordon of the Japanese Order of the Rising Sun on 29 August 1917.


title: John Jellicoe, 1st Earl Jellicoe

text: In June 1918, amidst concerns that—following the Treaty of Brest-Litovsk—the Germans were about to requisition the Russian Black Sea Fleet, Lloyd George proposed Jellicoe as Allied Supreme Naval Commander in the Mediterranean. The French were in favour of a combined Allied naval command, but the Italians were not, so nothing came of the suggestion.


title: John Jellicoe, 1st Earl Jellicoe

text: Jellicoe was promoted to Admiral of the Fleet on 3 April 1919. He became Governor-General of New Zealand in September 1920 and while there also served as Grand Master of New Zealand's Masonic Grand Lodge. Following his return to England, he was created Earl Jellicoe and Viscount Brocas of Southampton in the County of Southampton on 1 July 1925. He was made a Deputy Lieutenant of Hampshire in 1932. He died of pneumonia at his home in Kensington in London on 20 November 1935 and was buried in St Paul's Cathedral.


title: John Jellicoe, 1st Earl Jellicoe

text: In 1919, "Sleep, beneath the wave! a requiem" with words by Rev. Alfred Hall and Music by Albert Ham was "Dedicated to Admiral Viscount Jellicoe."


title: John Jellicoe, 1st Earl Jellicoe

text: The attempt of his official biographer, Admiral Reginald Bacon, to portray him as the conqueror of the U-Boats is, in John Grigg's view, absurd, as the main decisions were taken by other men. Bacon also claimed that his elevation to a viscountcy on dismissal was a deliberate snub, but in fact Sir John French, the former Commander-in-Chief of the BEF, was only a viscount at the time (both he and Jellicoe became Earls subsequently), whilst Fisher was never more than a Baron. Bacon's neutrality may be questionable as he had himself been sacked by Geddes from command of the Dover Patrol, replaced by Roger Keyes, shortly after Jellicoe's removal.


title: John Jellicoe, 1st Earl Jellicoe

text: Jellicoe married, at Holy Trinity Church, Sloane Street, on 1 July 1902, Florence Gwendoline Cayzer, daughter of the shipping magnate Sir Charles Cayzer. His brother, Rev. Frederick Jellicoe (1858–1927), conducted the service. Lord and Lady Jellicoe had a son and five daughters. His son George Jellicoe, 2nd Earl Jellicoe had a military career during the Second World War, after which he was a parliamentarian and a businessman.


title: Prince Sverre Magnus of Norway

text: Prince Sverre Magnus of Norway (born 3 December 2005) is the younger child of Crown Prince Haakon and Crown Princess Mette-Marit. He is third in line to succeed his grandfather King Harald V, after his father and elder sister Princess Ingrid Alexandra.


title: Prince Sverre Magnus of Norway

text: Prince Sverre Magnus was born on 3 December 2005 at The National Hospital the Oslo University Hospital in Oslo, where his sister Princess Ingrid Alexandra had been born a year earlier. He was baptised by Bishop Ole Christian Kvarme at the chapel of the Royal Palace in Oslo on 4 March 2006.


title: Prince Sverre Magnus of Norway

text: Beginning 18 August 2011, Sverre Magnus attended Jansløkka elementary school, a local state school attended by his sister and half-brother. On 17 June 2014, the Norwegian Royal Family notified the public that from the start of the 2014–2015 school year, Sverre Magnus would transfer to Oslo's private Montessori school. He attended the school until 2021. In the autumn of 2021, Sverre Magnus will attend in Oslo, the same school his older sister Princess Ingrid Alexandra currently attending, following the Information Technology and Media Production (IM) line.


title: Prince Sverre Magnus of Norway

text: Prince Sverre Magnus is known for dabbing on the balcony of the Royal Palace in the presence of the rest of the royal family, including his grandfather King Harald V. The dance move was performed unprompted.


title: Prince Sverre Magnus of Norway

text: The Constitution of Norway was amended in 1990 to introduce absolute primogeniture, ensuring that the crown would pass to the eldest child regardless of sex but keeping the Crown Prince ahead of his elder sister, Princess Märtha Louise. This change applied for the first time to the children of the Crown Prince, meaning that Sverre Magnus would not rank above his elder sister, as would have happened under prior constitutional rules. Sverre Magnus is third in the line of succession to the Norwegian throne following his sister. He is a member of the Royal Family but not of the Royal House, which consists only of his grandparents, parents and sister.


title: Prince Sverre Magnus of Norway

text: Prince Sverre Magnus is styled as "His Highness" Prince Sverre Magnus of Norway, as opposed to his sister, who is styled as "Her Royal Highness".


title: The Big Leap

text: The Big Leap is an American musical comedy-drama television series created by Liz Heldens, based on the British reality miniseries "Big Ballet", which aired on Fox during the 2021–22 television season. In March 2022, the series was canceled after one season.


title: The Big Leap

text: "The Big Leap" is a drama which revolved around a group of diverse, down-on-their-luck characters attempting to change their lives by participating in a potentially life-ruining reality dance show competition.


title: The Big Leap

text: On January 28, 2020, Fox gave the project a pilot order, the first for the network's 2020–21 television season, with Fox Entertainment and 20th Television set as co-production partners and was written by Liz Heldens. The series ultimately skipped the step to the 2021–22 television season due to the COVID-19 pandemic, with Fox giving a series greenlight on April 28, 2021. Heldens was set as showrunner with Jason Winer announced as director and executive producer of the pilot. On May 17, 2021, during Fox's Upfront presentation, it was confirmed that the series was scheduled to premiere as a fall season entry during the 2021–22 television season.


title: The Big Leap

text: In February 2020, Teri Polo, Matt Lucas, Ser'Darius Blain and Raymond Cham Jr. were cast in main roles for the pilot. In March 2020, Scott Foley was cast in the main role for this pilot including Simone Recasner and Jon Rudnitsky also joined the cast. On July 17, 2020, it was announced that Laura Benanti has been cast in the pilot. However, both Lucas and Benanti later exited the project. In December 2020, Piper Perabo was cast to replace Benanti in the lead role, with Mallory Jansen and Kevin Daniels joining the series in a main role. After the series was picked up in May 2021, Anna Grace Barlow joined the series. In July 2021, Adam Kaplan, Tom Lennon, and Robert Wisdom joined the cast in recurring roles. In October 2021, Brett Tucker joined the cast in a recurring role.


title: The Big Leap

text: Production of the pilot episode commenced on December 2, 2020. On December 18, 2020, production was temporarily suspended due to positive COVID-19 test results, from the crew members. The pilot was filmed in Chicago, Illinois, and at the "Rialto Theatre" in downtown Joliet.


title: The Big Leap

text: The series premiered on Fox on September 20, 2021 and concluded on December 6, 2021. In Canada, the series airs on CTV2. The series premiered on Disney+ via the streaming hub Star as an original series in selected countries. In Latin America, the series premiered as a Star+ original.


title: The Big Leap

text: On March 4, 2022, multiple media outlets reported that Fox had canceled "The Big Leap" after a single season; despite critical acclaim, it had been the network's lowest rated series in the 2021–22 season.


title: The Big Leap

text: Due to unknown reasons, the show was removed from all Disney streaming plaforms on October 3, 2022, alongside other original Star shows.


title: The Big Leap

text: On Rotten Tomatoes, the series holds an approval rating of 100% with an average rating of 8.50/10, based on 16 critic reviews. The website's critics consensus states, ""The Big Leap"s joyous celebration of life and love isn't remotely subtle, but with moves like this and charm to spare, why play coy?" On Metacritic, it has a weighted average score of 73 out of 100, based on 11 critics, indicating "generally favorable reviews".


title: Degree (music)

text: In music theory, the scale degree is the position of a particular note on a scale relative to the tonic, the first and main note of the scale from which each octave is assumed to begin. Degrees are useful for indicating the size of intervals and chords and whether an interval is major or minor.


title: Degree (music)

text: In the most general sense, the scale degree is the number given to each step of the scale, usually starting with 1 for tonic. Defining it like this implies that a tonic is specified. For instance, the 7-tone diatonic scale may become the major scale once the proper degree has been chosen as tonic (e.g. the C-major scale C–D–E–F–G–A–B, in which C is the tonic). If the scale has no tonic, the starting degree must be chosen arbitrarily. In set theory, for instance, the 12 degrees of the chromatic scale usually are numbered starting from C=0, the twelve pitch classes being numbered from 0 to 11.


title: Degree (music)

text: In a more specific sense, scale degrees are given names that indicate their particular function within the scale (see table below). This implies a functional scale, as is the case in tonal music.


title: Degree (music)

text: This example gives the names of the functions of the scale degrees in the seven note diatonic scale. The names are the same for the major and minor scales, only the seventh degree changes name when flattened:


title: Degree (music)

text: The term scale step is sometimes used synonymously with scale degree, but it may alternatively refer to the distance "between" two successive and adjacent scale degrees (see steps and skips). The terms "whole step" and "half step" are commonly used as interval names (though "whole scale step" or "half scale step" are not used). The number of scale degrees and the distance between them together define the scale they are in.


title: Degree (music)

text: In Schenkerian analysis, "scale degree" (or "scale step") translates Schenker's German "Stufe", denoting "a chord having gained structural significance" (see Schenkerian analysis#Harmony).


title: Victor-class submarine

text: The Victor class, Soviet designations Project 671 "Yorsh, Project 671RT "Syomga and Project 671RTM/RTMK "Shchuka", (NATO reporting names Victor I, Victor II and Victor III, respectively), are series of nuclear-powered attack submarines built in the Soviet Union and operated by the Soviet Navy. Since the 1960s, 48 units were built in total, of which the last remaining are currently in service with the Russian Navy. The Victor-class submarines featured a teardrop shape, allowing them to travel at high speed. These vessels were primarily designed to protect Soviet surface fleets and to attack American ballistic missile submarines. Project 671 began in 1959 with the design task assigned to SKB-143 (one of the predecessors of the Malakhit Marine Engineering Bureau).


title: Victor-class submarine

text: Soviet designation Project 671 "Yorsh" (ruffe)—was the initial type that entered service in 1967; 16 were produced. Each had six torpedo tubes for launching Type 53 torpedoes and SS-N-15 anti-submarine missiles and mines could also be released. Subs had a capacity of 24 tube-launched weapons or 48 mines (or a combination). They were long. All disposed.


title: Victor-class submarine

text: Soviet designation Project 671RT "Syomga" (atlantic salmon)—entered service in 1972; seven were produced in the 1970s. These were originally designated Uniform class by NATO. They had similar armament to the Victor I class and were the first Soviet submarines to introduce raft mounting for acoustic quieting. Production was truncated due to a decision to develop the improved Victor III class. They were long. All disposed.


title: Victor-class submarine

text: Soviet designation Project 671RTM/RTMK "Shchuka" (pike)—entered service in 1979; 25 were produced until 1991. Quieter than previous Soviet submarines, these ships had four tubes for launching SS-N-21 or SS-N-15 missiles and Type 53 torpedoes, plus another two tubes for launching SS-N-16 missiles and Type 65 torpedoes. 24 tube-launched weapons or 36 mines could be on board. The Victor III class caused a minor furor in NATO intelligence agencies at its introduction because of the distinctive pod on the vertical stern-plane. Speculation immediately mounted that the pod was the housing for some sort of exotic silent propulsion system, possibly a magnetohydrodynamic drive unit. Another theory proposed that it was some sort of weapon system. In the end, the pod was identified as a hydrodynamic housing for a reelable towed passive sonar array; the system was subsequently incorporated into the and SSNs. In October 1983 the towed array of , a Victor III operating west of Bermuda, became tangled with the towed array of US frigate . "K-324" was forced to surface, allowing NATO forces to photograph the pod in its deployed state. The Victor-III class was continuously improved during construction and late production models have a superior acoustic performance. They were long. 21 disposed.


title: Bavarian cream

text: Bavarian cream, crème bavaroise or simply bavarois is a dessert consisting of milk thickened with eggs and gelatin or isinglass, into which whipped cream is folded. The mixture sets up in a cold mold and is unmolded for serving. Earlier versions, sometimes called fromage bavarois, did not include eggs.


title: Bavarian cream

text: Bavarian cream is a classic dessert that was included in the repertoire of chef Marie-Antoine Carême, who is sometimes credited with it. It was named in the early 19th century for Bavaria or, perhaps more likely in the history of haute cuisine, for a particularly distinguished visiting Bavarian, such as a Wittelsbach.


title: Bavarian cream

text: In the United States, Bavarian creams first appeared in Boston Cooking School books by D. A. Lincoln in 1884, and by Fannie Farmer in 1896.


title: Bavarian cream

text: Bavarian cream is lightened with whipped cream when on the edge of setting up and before it is molded; a true bavarian cream is usually filled into a fluted mold, chilled until firm, then turned out onto a serving plate. By coating a chilled mold first with a fruit gelatin, a glazed effect can be produced. Imperfections in the unmolding are disguised with strategically placed fluted piping of whipped cream. In the United States, it is common to serve Bavarian Cream directly from the bowl it has been chilled in, similar to a French mousse. In this informal presentation, Escoffier recommended the bavarian cream be made in a "timbale or deep silver dish which is then surrounded with crushed ice".


title: Bavarian cream

text: It may be served with a fruit sauce or a raspberry or apricot purée or used to fill elaborate charlottes.


title: Bavarian cream

text: Though it does not pipe smoothly because of its gelatin, it could substitute for pastry cream as a filling for doughnuts. Some American "Bavarian Cream doughnuts" are filled with a version of a crème pâtissière (pastry cream), some are filled with true "bavarois". The "Bavarian Cream" part of the name refers to the type of doughnut filling, with doughnuts including chocolate-frosted and non-chocolate-frosted varieties. Spellings of "cream" may differ, such as the Bavarian Crème Bismark from Seattle-based Top Pot Doughnuts.


title: Clitoral hood reduction

text: Clitoral hood reduction, also termed clitoral hoodectomy, clitoral unhooding, clitoridotomy, or (partial) hoodectomy, is a plastic surgery procedure for reducing the size and the area of the clitoral hood (prepuce) in order to further expose the clitoral glans of the clitoris.


title: Clitoral hood reduction

text: It is usually performed as an elective cosmetic surgery meant to improve sexual satisfaction and to change the aesthetic appearance of the vulva. The reduction of the clitoral hood usually is done together with a labiaplasty that reduces the labia minora, and occasionally within a vaginoplasty.


title: Clitoral hood reduction

text: Though patient surveys have indicated satisfaction with the outcome of such procedures, the American College of Obstetricians and Gynecologists cautioned in 2007 that for this type of vaginal surgeries, which are not medically indicated, women should be informed about the lack of data on their efficacy and potential complications.


title: Clitoral hood reduction

text: The procedures for labiaplasty occasionally include a clitoral hood reduction. One technique for reducing the clitoral hood is the bilateral excision (cutting) of the prepuce tissues covering the clitoral glans, with especial attention to maintaining the glans in the midline. Another technique cuts away (excises) the redundant folds of clitoral prepuce tissue, with incisions parallel to the long axis of the clitoris.


title: Clitoral hood reduction

text: Clitoral hood reduction can be included in the extended wedge resection labiaplasty technique, wherein the extension of the exterior wedge sections is applied to reducing the prepuce tissues of the clitoral glans. Yet, occasionally excess prepuce-skin, in the center of the clitoral hood, is removed with separate incisions.