AAAI Publications, Twenty-Second International FLAIRS Conference

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A Generalized Heuristic for Can't Stop
James R. Glenn, Christian J. Aloi

Last modified: 2009-03-18


Can't Stop is a jeopardy stochastic game played on an octagonal game board with four six-sided dice. Optimal strategies have been computed for some simplified versions of Can't Stop by employing retrograde analysis and value iteration combined with Newton's method. These computations result in databases that map game positions to optimal moves. Solving the original game, however, is infeasible with current techniques and technology. This paper describes the creation of heuristic strategies for solitaire Can't Stop by generalizing an existing heuristic and using genetic algorithms to optimize the generalized parameters. The resulting heuristics are easy to use and outperform the original heuristic by 19%. Results of the genetic algorithm are compared to the known optimal results for smaller versions of Can't Stop, and data is presented showing the relative insensitivity of the particular genetic algorithm used to the balance between reduced noise and increased population diversity.


genetic algorithms; jeopardy stochastic games; heuristics

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