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Learning from Perfection

A Data Mining Approach to Evaluation Function Learning in Awari
  • Jack van Rijswijck
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2063)

Abstract

Automatic tuning of evaluation function parameters for game playing programs, and automatic discovery of the very features that these parameters refer to, are challenging but potentially very powerful tools. While some advances have been made in parameter tuning, the field of feature discovery is still in its infancy. The game ofAwari offers the possibility to achieve both goals. This paper describes the efforts to design an evaluation function without any human expertise as part of the Awari playing program Bambam, as being developed by the Awari team1 at the University of Alberta.

Keywords

Machine learning heuristic search game playing alpha-beta Awari 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Jack van Rijswijck
    • 1
  1. 1.Department of Computing ScienceUniversity of AlbertaEdmontonCanada

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