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Alpha-Beta Search Revisited

  • Paul Parkins
  • John A. Keane
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2412)

Abstract

An algorithm, Aspiration Scout/MTD(f), is derived from an analysis of alpha-beta (α-β) tree search. When compared to its predecessors, it results in an average 10.1% reduction in search effort with a best case of 17.4%. 1 The search space is usually referred to as a tree, however in games such as chess and draughts it is actually a directed acyclic graph (DAG). Programs search a dynamically unfolding DAG.

Keywords

Leaf Node Directed Acyclic Graph Search Effort Node Count Interior Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Eppstein, D.: Strategy and Board Game Programming Lecture Notes, 1997 http://www.ics.uci/~eppstein/180a/s97.html.
  2. 2.
    Plaat, A., et al: Exploiting Graph Properties of Game Trees, AAAI, 1996.Google Scholar
  3. 3.
    Schaeffer, J.: The History Heuristic and Alpha-Beta Enhancements in Practice, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 11, 1989.Google Scholar
  4. 4.
    Schaeffer, J., Plaat, A.: New Advances in Alpha-Beta Searching, Proceedings of the 24th ACM Computer Science Conference, 1996.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Paul Parkins
    • 1
  • John A. Keane
    • 1
  1. 1.Department of ComputationUMISTManchesterUK

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