Transposition Table Driven Work Scheduling in Distributed Game-Tree Search

Authors:
Akihiro Kishimoto;Jonathan Schaeffer
Affiliations:
-;-
Venue:
AI '02 Proceedings of the 15th Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Year:
2002

Citing 7
Cited 1

Distributed game-tree searching

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Transposition table driven work scheduling in distributed search

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A Performance Analysis of Transposition-Table-Driven Work Scheduling in Distributed Search

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Asynchronous parallel game-tree search

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Relative efficiency of alpha-beta implementations

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Satin: A high-level and efficient grid programming model

ACM Transactions on Programming Languages and Systems (TOPLAS)

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Abstract

MTD(f) is a new variant of the 驴脽 algorithm that has become popular amongst practitioners. TDS is a new parallel search algorithm that has proven to be effective in the single-agent domain. This paper presents TDSAB, applying the ideas behind TDS parallelism to the MTD(f) algorithm. Results show that TDSAB gives comparable performance to that achieved by conventional parallel 驴脽 algorithms. This result is very encouraging, given that traditional parallel 驴脽 approaches appear to be exhausted, while TDSAB opens up new opportunities for further performance improvements.