A survey on the need and use of AI in game agents
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paper_title: The state of the art in game AI standardisation

paper_content:

The Artificial Intelligence Interface Standards Committee (AIISC) was formed in 2002 to develop interface standards for AI middleware in the computer game industry. In this paper, we provide an overview of the work completed to date by the working groups making up the AIISC. We describe the issues each group is addressing and examine their relevance and importance to the domain of computer games development, and discuss their benefits and shortcomings. We also outline the current progress of each group, and the direction they will be taking in the future in order to implement a useable and widely accepted game AI API.
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paper_title: SORTS: A Human-Level Approach to Real-Time Strategy AI

paper_content:

We developed knowledge-rich agents to play real-time strategy games by interfacing the ORTS game engine to the Soar cognitive architecture. The middleware we developed supports grouping, attention, coordinated path finding, and FSM control of low-level unit behaviors. The middleware attempts to provide information humans use to reason about RTS games, and facilitates creating agent behaviors in Soar. Agents implemented with this system won two out of three categories in the AIIDE 2006 ORTS competition.
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paper_title: Research Directions for AI in Computer Games

paper_content:

The computer games industry is now bigger than the film industry. Until recently, technology in games was driven by a desire to achieve real-time, photo-realistic graphics. To a large extent, this has now been achieved. As game developers look for new and innovative technologies to drive games development, AI is coming to the fore. This paper will examine how sophisticated AI techniques, such as those being used in mainstream academic research, can be applied to computer games and introduce three projects doing just that.
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paper_title: Incremental Case-Based Plan Recognition Using State Indices

paper_content:

We describe a case-based approach to the keyhole plan-recognition task where the observed agent is a state-space planner whose world states can be monitored. Case-based approach provides means for automatically constructing the plan library from observations, minimizing the number of extraneous plans in the library. We show that the knowledge about the states of the observed agent's world can be effectively used to recognize agent's plans and goals, given no direct knowledge about the planner's internal decision cycle. Cases (plans) containing state knowledge enable the recognizer to cope with novel situations for which no plans exist in the plan library, and to further assist in effective discrimination among competing plan hypothesis.
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paper_title: Research Directions for AI in Computer Games

paper_content:

The computer games industry is now bigger than the film industry. Until recently, technology in games was driven by a desire to achieve real-time, photo-realistic graphics. To a large extent, this has now been achieved. As game developers look for new and innovative technologies to drive games development, AI is coming to the fore. This paper will examine how sophisticated AI techniques, such as those being used in mainstream academic research, can be applied to computer games and introduce three projects doing just that.
---
paper_title: Research Directions for AI in Computer Games

paper_content:

The computer games industry is now bigger than the film industry. Until recently, technology in games was driven by a desire to achieve real-time, photo-realistic graphics. To a large extent, this has now been achieved. As game developers look for new and innovative technologies to drive games development, AI is coming to the fore. This paper will examine how sophisticated AI techniques, such as those being used in mainstream academic research, can be applied to computer games and introduce three projects doing just that.
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Title: A Survey on the Need and Use of AI in Game Agents

Section 1: INTRODUCTION
Description 1: Introduce the use of game agents and NPCs, define what makes an agent, and set the context for investigating the use of AI in game agents.

Section 2: Goal-based agents
Description 2: Discuss what goal-based agents are, provide examples, and explain how planning and goal-directed behavior benefit game agents.

Section 3: GAME AI IN GENERAL
Description 3: Discuss the general aims and methodologies of game AI, including scripting, pathfinding, emergent AI, learning, and reasoning.

Section 4: Game AI specific to different genres: NPC behaviors, AI methodologies in use, expected AI challenges
Description 4: Examine the specific needs and behaviors of AI for different game genres such as RPGs, FPS, RTS, God games, and Action-Adventure games, and discuss the methodologies used.

Section 5: EVALUATION OF GAMES FOR THEIR AGENT CHARACTERISTICS
Description 5: Evaluate popular games based on agent characteristics like reactivity, autonomy, and goal-orientation, and discuss their AI implementations.

Section 6: CONCLUSIONS AND DISCUSSION
Description 6: Summarize the findings on whether NPCs can be considered game agents, discuss the AI methodologies used in commercial games, and highlight areas for further investigation.