Title :
Evolving both search and strategy for Reversi players using genetic programming
Author :
Benbassat, Amit ; Sipper, Moshe
Author_Institution :
Dept. of Comput. Sci., Ben-Gurion Univ., Beer-Sheva, Israel
Abstract :
We present the application of genetic programming to the zero-sum, deterministic, full-knowledge board game of Reversi. Expanding on our previous work on evolving boardstate evaluation functions, we now evolve the search algorithm as well, by allowing evolved programs control of game-tree pruning. We use strongly typed genetic programming, explicitly defined introns, and a selective directional crossover method. We show that our system regularly churns out highly competent players and our results prove easy to scale.
Keywords :
computer games; genetic algorithms; search problems; trees (mathematics); Reversi players; deterministic board game; full-knowledge board game; game-tree pruning; genetic programming; search algorithm; selective directional crossover method; zero-sum board game; Games; Genetic algorithms; Genetics; Humans; Receivers; Sociology; Statistics;
Conference_Titel :
Computational Intelligence and Games (CIG), 2012 IEEE Conference on
Conference_Location :
Granada
Print_ISBN :
978-1-4673-1193-9
Electronic_ISBN :
978-1-4673-1192-2
DOI :
10.1109/CIG.2012.6374137