Advertisement

Move Ordering Using Neural Networks

  • Levente Kocsis
  • Jos Uiterwijk
  • Jaap van den Herik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2070)

Abstract

The efficiency of alpha-beta search algorithms heavily de- pends on the order in which the moves are examined. This paper focuses on using neural networks to estimate the likelihood of a move being the best in a certain position. The moves considered more likely to be the best are examined first. We selected Lines of Action as a testing ground. We investigated several schemes to encode the moves in a neural net- work. In the experiments, the best performance was obtained by using one output unit for each possible move of the game. The results indicate that our move-ordering approach can speed up the search with 20 to 50 percent compared with one of the best current alternatives, the history heuristic.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Greer, K.: Computer Chess Move-Ordering Schemes using Move Influence. Artificial Intelligence 120 (2000) 235–250zbMATHCrossRefGoogle Scholar
  2. 2.
    Kocsis, L., Uiterwijk, J. W. H. M., Herik, H. J. van den: Learning Time Allocation using Neural Networks. Working Notes of the Second International Conference on Computers and Games (2000) 297–314Google Scholar
  3. 3.
    Riedmiller, M., Braun, H.: A Direct Adaptive Method for Faster Backpropagation Learning: The RPROP Algorithm. Proceedings of the IEEE International Conference on Neural Networks 1993 (ICNN 93) (1993) 586–591Google Scholar
  4. 4.
    Schaeffer, J.: The History Heuristic. ICCA Journal 6(3) (1983) 16–19Google Scholar
  5. 5.
    Winands, M. H. M.: Analysis and Implementation of Lines of Action. MSc thesis CS 00-03, Department of Computer Science, Universiteit Maastricht (2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Levente Kocsis
    • 1
  • Jos Uiterwijk
    • 1
  • Jaap van den Herik
    • 1
  1. 1.Department of Computer ScienceInstitute for Knowledge and Agent Technology, Universiteit MaastrichtMaastrichtThe Netherlands

Personalised recommendations