Opponent-based tactic selection for a first person shooter game (2011)
Type of ContentConference Contributions - Published
PublisherUniversity of Canterbury. Computer Science and Software Engineering
Video games are quickly becoming a significant part of society with a growing industry that employs a wide range of talent, from programmers to graphic artists. Video games are also becoming an interesting and useful testbed for Artificial Intelligence research. Complex, realistic environmental constraints, as well as performance considerations demand highly efficient AI techniques. At the same time, the AI component of a video game may define the ongoing commercial success, or failure, of a particular game or game engine. This research details an approach to opponent modeling in a first person shooter game, and evaluates proficiency gains facilitated by such a technique. Information about the user is recorded and used by the existing Artificial Intelligence component to select tactics for any given opponent. The evaluation results show that when computer characters use such modeling they are more effective than when they do not model their opponent.)
CitationThomson, D., Mitrovic, A. (2011) Opponent-based tactic selection for a first person shooter game. Rome, Italy: 3rd International Conference on Agents and Artificial Intelligence, 28-30 Jan 2011. 591-594.
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KeywordsOpponent modeling; Adaptive AI; Machine learning; Student modeling; Video games; Quake 3
ANZSRC Fields of Research08 - Information and Computing Sciences::0801 - Artificial Intelligence and Image Processing::080199 - Artificial Intelligence and Image Processing not elsewhere classified
08 - Information and Computing Sciences::0806 - Information Systems::080602 - Computer-Human Interaction
08 - Information and Computing Sciences::0803 - Computer Software::080305 - Multimedia Programming
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