History mechanism supported differential evolution for chess evaluation function tuning

  • Authors:

  • B. Bošković;J. Brest;A. Zamuda;S. Greiner;V. Žumer

  • Affiliations:

  • University of Maribor, Faculty of Electrical Engineering and Computer Science, Smetanova ul. 17, 2000, Maribor, Slovenia;University of Maribor, Faculty of Electrical Engineering and Computer Science, Smetanova ul. 17, 2000, Maribor, Slovenia;University of Maribor, Faculty of Electrical Engineering and Computer Science, Smetanova ul. 17, 2000, Maribor, Slovenia;University of Maribor, Faculty of Electrical Engineering and Computer Science, Smetanova ul. 17, 2000, Maribor, Slovenia;University of Maribor, Faculty of Electrical Engineering and Computer Science, Smetanova ul. 17, 2000, Maribor, Slovenia

  • Venue:
  • Soft Computing - A Fusion of Foundations, Methodologies and Applications
  • Year:
  • 2010

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Abstract

This paper presents a differential evolution (DE) based approach to chess evaluation function tuning. DE with opposition-based optimization is employed and upgraded with a history mechanism to improve the evaluation of individuals and the tuning process. The general idea is based on individual evaluations according to played games through several generations and different environments. We introduce a new history mechanism which uses an auxiliary population containing good individuals. This new mechanism ensures that good individuals remain within the evolutionary process, even though they died several generations back and later can be brought back into the evolutionary process. In such a manner the evaluation of individuals is improved and consequently the whole tuning process.