Tournament Particle Swarm Optimization

W. H. Duminy, A. Engelbrecht
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引用次数: 1

Abstract

This paper introduces tournament particle swarm optimization (PSO) as a method to optimize weights of game tree evaluation functions in a competitive environment using particle swarm optimization. This method makes use of tournaments to ensure a fair evaluation of the performance of particles in the swarm, relative to that of other particles. The empirical work presented compares the performance of different tournament methods that can be applied to the tournament PSO, with application to Checkers.
锦标赛粒子群优化
本文介绍了竞赛粒子群算法(PSO)作为一种利用粒子群算法优化竞争环境下博弈树评价函数权重的方法。这种方法利用比赛来确保群体中粒子相对于其他粒子的性能得到公平的评估。本文的实证工作比较了不同比赛方法的性能,这些方法可以应用于比赛PSO,并应用于跳棋。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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