From the early days of AI, computers have been programmed to play games against human players. Most of the AI work has sought to build world-champion programs to play turn-based games such as Chess and Checkers, however computer games increasingly provide for entertaining real-time play. In this dissertation, we present an extension of recursive game theory, which can be used to analyze games involving simultaneous movement. We include an algorithm which can be used to practically solve recursive games, and present a proof of its correctness. We also define a game theory of lowered expectations to deal with situations where game theory currently fails to give players a definitive strategy, and demonstrate its applicability using several example games.
|Advisor:||Chester, Daniel L.|
|Commitee:||Case, John, Heniz, Jeffrey N., McCoy, Kathleen F.|
|School:||University of Delaware|
|Department:||Computer and Information Sciences|
|School Location:||United States -- Delaware|
|Source:||DAI-B 77/02(E), Dissertation Abstracts International|
|Subjects:||Applied Mathematics, Mathematics, Computer science|
|Keywords:||Concurrent reachability games, Game ai, Game theory, General game playing, Recursive games|
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