Not Logged In

Transposition Table Driven Work Scheduling in Distributed Game-Tree Search

Full Text: ai02.ps PS

MTD(f) is a new variant of the aB algorithum 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) algorithym. Results show that TDSAB gives comparable performance to that achieved by conventional parallel aB algorithms. This appear to be exhausted, while TDSAB opens up new opportunities for further performance improvements.

Citation

A. Kishimoto, J. Schaeffer. "Transposition Table Driven Work Scheduling in Distributed Game-Tree Search". Canadian Society for Computational Studies of Intelligence, January 2002.

Keywords: machine learning
Category: In Conference

BibTeX

@incollection{Kishimoto+Schaeffer:CSCSI02,
  author = {Akihiro Kishimoto and Jonathan Schaeffer},
  title = {Transposition Table Driven Work Scheduling in Distributed Game-Tree
    Search},
  booktitle = {Canadian Society for Computational Studies of Intelligence},
  year = 2002,
}

Last Updated: June 05, 2007
Submitted by Staurt H. Johnson

University of Alberta Logo AICML Logo