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 :
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