Designing artificial tetris players with evolution strategies and racing

Authors:
Amine Boumaza
Affiliations:
Univ. Lille Nord de France, F-59000 Lille, ULCO, LISIC, F-62100 Calais, France
Venue:
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Year:
2011

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Abstract

This article describes how racing procedures in evolution strategies can help reduce the number of evaluations. This idea is illustrated on learning Tetris players which can be addressed as a stochastic optimization problem. Different experiments show the benefits of the racing procedures in evolution strategies which can significantly reduce the number of evaluations.