A Skat Player Based on Monte-Carlo Simulation

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A Skat Player Based on Monte-Carlo Simulation
We apply Monte Carlo simulation and alpha-beta search to the card game of Skat, which is similar to Bridge, but different enough to require some new algorithmic ideas besides the techniques developed for Bridge. Our Skatplaying program integrates well-known techniques such as move ordering with two new search enhancements. Quasi-symmetry reduction generalizes symmetry reductions, popularized by Ginsberg's Partition Search algorithm, to search states which are "almost equivalent". Adversarial heuristics generalize ideas from single-agent search algorithms like A to two-player games, leading to guaranteed lower and upper bounds for the score of a game position. Combining these techniques with state-of-the-art tree search algorithms, our program determines the game-theoretical value of a typical Skat hand (with perfect information) in 10 milliseconds.
Sebastian Kupferschmid, Malte Helmert
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where CG
Authors Sebastian Kupferschmid, Malte Helmert
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