AAAI Publications, Thirtieth AAAI Conference on Artificial Intelligence

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Learning and Using Hand Abstraction Values for Parameterized Poker Squares
Todd W. Neller, Colin M. Messinger, Zuozhi Yang

Last modified: 2016-03-05

Abstract


We describe the experimental development of an AI player that adapts to different point systems for Parameterized Poker Squares. After introducing the game and research competition challenge, we describe our static board evaluation utilizing learned evaluations of abstract partial Poker hands. Next, we evaluate various time management strategies and search algorithms. Finally, we show experimentally which of our design decisions most signicantly accounted for observed performance.

Keywords


game artificial intelligence; reinforcement learning; expectimax

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