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CS299 ProposalIntelligent Behavior for Computer Game Characters Using Prediction and LearningLeo Lee (leo@leolees.com) Advisor: Dr. Chris Pollett (cpollett@yahoo.com) Committee Members: Dr. Rudy Rucker (rudy@rudyrucker.com) and Dr. Jeff Smith (smithJ@cs.sjsu.edu) Abstract:While the graphical aspect of video games has seen much improvement, sophisticated AI in video games is still a rarity. The standard for video game AI has been based on elaborate finite state machines (FSMs). The use of FSMs for video game AI leads to static behavior in the computer controlled non-player characters (NPCs). In turn, this static behavior detracts from the playability and entertainment value of the game. The purpose of this thesis is to develop an AI system for a computer game, which will allow the NPC to learn and adapt its behavior to the player. The game itself will be a 3D fighting game called Alpha Fighter. The player will control one character while the computer AI system controls the other. Each character will have a variety of fighting moves, which can be used to defeat the opponent. The goal is to have the AI fighter behave more like a human player would. The AI fighter will dynamically learn and adapt its behavior according to the behavior of the human player. In essence, the AI fighter will attempt to behave like a human player, making predictions of its opponent based on observations, and formulating strategies based on those predictions. To achieve this, a Hidden Markov Model or Dynamic Bayesian Network will be used. CS297 Results
Proposed Schedule
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Innovations and Challenges
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