Abstract
\(\alpha \mu \) is an anytime heuristic search algorithm for incomplete information games that assumes perfect information for the opponents. \(\alpha \mu \) addresses and if given enough time solves the strategy fusion and the non-locality problems encountered by Perfect Information Monte Carlo search (PIMC). Strategy fusion is due to PIMC playing different strategies in different worlds when it has to find a unique strategy for all the worlds. Non-locality is due to choosing locally optimal moves that are globally inferior. In this paper \(\alpha \mu \) is applied to the game of Bridge and outperforms PIMC.
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Notes
- 1.
It is an acceptable simplification of the real scoring of Bridge. At Bridge, the declarer has to make six more tricks than the number in his contract.
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Acknowledgment
Thanks to Alexis Rimbaud for explaining me how to use the solver of Bo Haglund and to Bo Haglund for his Double Dummy Solver.
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Cazenave, T., Ventos, V. (2021). The \(\alpha \mu \) Search Algorithm for the Game of Bridge. In: Cazenave, T., Teytaud, O., Winands, M.H.M. (eds) Monte Carlo Search. MCS 2020. Communications in Computer and Information Science, vol 1379. Springer, Cham. https://doi.org/10.1007/978-3-030-89453-5_1
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