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2021 | OriginalPaper | Chapter

The \(\alpha \mu \) Search Algorithm for the Game of Bridge

Authors : Tristan Cazenave, Véronique Ventos

Published in: Monte Carlo Search

Publisher: Springer International Publishing

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Abstract

The chapter introduces an innovative search algorithm designed to tackle the complexities of imperfect information games, specifically the game of Bridge. It addresses the challenges of strategy fusion and non-locality, which have hindered the development of superhuman AI for such games. The algorithm, named , is an improvement over existing methods like Perfect Information Monte Carlo (PIMC) and other related search algorithms. It offers an anytime heuristic search that can solve the strategy fusion problem exactly given enough time and provides an anytime solution to the non-locality problem using Pareto fronts of vectors representing outcomes for different possible worlds. The algorithm includes optimizations like early and root cuts, and the use of a transposition table to speed up the search. Experimental results demonstrate that outperforms PIMC, achieving a higher win rate in Bridge games. The chapter concludes with a discussion of future work, including potential improvements and applications of the algorithm.
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Metadata
Title
The Search Algorithm for the Game of Bridge
Authors
Tristan Cazenave
Véronique Ventos
Copyright Year
2021
Book
Monte Carlo Search

Print ISBN: 978-3-030-89452-8

Electronic ISBN: 978-3-030-89453-5

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-89453-5_1

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