DocumentCode
1230339
Title
Genetically evolved strategies. Winning by selective processing of the chromosome pool
Author
Sgarbas, Kyriakas ; Fakotakis, Nikos ; Kokkinakis, George
Author_Institution
Dept. of Electr. Eng., Patras Univ., Greece
Volume
14
Issue
1
fYear
1995
Firstpage
36
Lastpage
40
Abstract
Describes how the authors used genetic algorithms (GAs) to make a computer develop its own strategy in playing a simple board game. There are various types of games. John von Neumann and Oskar Morgenstern´s Game Theory classifies games into several categories depending on the number of players involved, the presence or absence of the element of chance, the case that all players receive the same pieces of information or not and the type of payment function. The authors consider two-person zero-sum non-chance perfect-infermation games. Chess and checkers belong to this class
Keywords
game theory; games of skill; genetic algorithms; checkers; chess; genetic algorithms; genetically evolved strategies; selective processing; simple board game; two-person zero-sum nonchance perfect-infermation games; Artificial intelligence; Biological cells; Books; Game theory; Humans; Integrated circuit modeling; Integrated circuit testing; Minimax techniques; Radio access networks;
fLanguage
English
Journal_Title
Potentials, IEEE
Publisher
ieee
ISSN
0278-6648
Type
jour
DOI
10.1109/45.350567
Filename
350567
Link To Document