Tournament Particle Swarm Optimization

被引：0
|
作者：
Duminy, Willem H. [1 ]
Engelbrecht, Andries P. [1 ]
机构：
[1] Univ Pretoria, Dept Comp Sci, ZA-0002 Pretoria, South Africa
来源：
2007 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND GAMES | 2007年
关键词：
PSO; machine learning; game playing; tournament; competitive co-evolution;
D O I：
10.1109/CIG.2007.368091
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：146 / 153
页数：8
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