DocumentCode
3257096
Title
Using genetic programming to evolve board evaluation functions
Author
Ferrer, Gabriel J. ; Martin, W.N.
Author_Institution
Dept. of Comput. Sci., Virginia Univ., Charlottesville, VA, USA
Volume
2
fYear
1995
fDate
29 Nov-1 Dec 1995
Firstpage
747
Abstract
Employs the genetic programming paradigm to enable a computer to learn to play strategies for the ancient Egyptian boardgame Senet by evolving board evaluation functions. Formulating the problem in terms of board evaluation functions made it feasible to evaluate the fitness of game playing strategies by using tournament-style fitness evaluation. The game has elements of both strategy and chance. Our approach learns strategies which enable the computer to play consistently at a reasonably skillful level
Keywords
game theory; games of skill; genetic algorithms; learning (artificial intelligence); Senet; ancient Egyptian boardgame; board evaluation functions evolution; chance; game playing strategy learning; genetic programming; skill level; tournament-style fitness evaluation; Algorithm design and analysis; Artificial intelligence; Computer science; Functional programming; Genetic programming; Machine intelligence; Random number generation; Roads; Strategic planning; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2759-4
Type
conf
DOI
10.1109/ICEC.1995.487479
Filename
487479
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