Anton*, Calin

Castro-Wunsch, Karo

Maga, William

English

MacEwan Open Journals (MacEwan University)

AI	Algorithms	and	Stochastic	Game‐play  Karo Castro-Wunsch, William Maga, Calin Anton*  MacEwan University  ORAL Innovation  Solving Stochastic Problem-Spaces, which have large branching factors, require specialized algorithms to deal with. We investigated Poker Squares, and many variations thereof, to determine an ideal algorithmic approach. We implemented and evaluated several designs: Rule-Based, Expectimax, Monte Carlo Simulation based Reinforcement Learning, State Evaluation, and Upper Confidence Threshold (UCT) Policies. In this presentation we describe our implementations of these designs, as well as the results of a tournament-style competition. The results are used to determine the best algorithm design for the specific problem found within Poker Squares. The algorithms that are designed, and the problem space of Poker Squares, are analyzed with respect to the real world.   

AI Algorithms and Stochastic Game‐play

https://journals.macewan.ca/ursca/article/download/340/258

AI Algorithms and Stochastic Game‐play

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MacEwan Open Journals (MacEwan University)