DocumentCode
412552
Title
Comparing PSO structures to learn the game of checkers from zero knowledge
Author
Franken, Nelis ; Engelbrecht, Andries P.
Author_Institution
Dept. of Comput. Sci., Pretoria Univ., South Africa
Volume
1
fYear
2003
fDate
8-12 Dec. 2003
Firstpage
234
Abstract
This paper investigates the effectiveness of various particle swarm optimiser structures to learn how to play the game of checkers. Co-evolutionary techniques are used to train the game playing agents. Performance is compared against a player making moves at random. Initial experimental results indicate definite advantages in using certain information sharing structures and swarm size configurations to successfully learn the game of checkers.
Keywords
cooperative systems; evolutionary computation; games of skill; learning (artificial intelligence); optimisation; tree searching; PSO structures; checkers game; coevolutionary techniques; game playing agents; information sharing structures; particle swarm optimiser; random movement; swarm size configurations; zero knowledge; Africa; Computer science; Databases; Law; Legal factors; Machine learning; Minimax techniques; Neural networks; Particle swarm optimization; Spine;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN
0-7803-7804-0
Type
conf
DOI
10.1109/CEC.2003.1299580
Filename
1299580
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