DocumentCode :
2910118
Title :
Evolving diverse Ms. Pac-Man playing agents using genetic programming
Author :
Alhejali, Atif M. ; Lucas, Simon M.
Author_Institution :
Game Intell. Group, Univ. of Essex, Colchester, UK
fYear :
2010
fDate :
8-10 Sept. 2010
Firstpage :
1
Lastpage :
6
Abstract :
This paper uses genetic programming (GP) to evolve a variety of reactive agents for a simulated version of the classic arcade game Ms. Pac-Man. A diverse set of behaviours were evolved using the same GP setup in three different versions of the game. The results show that GP is able to evolve controllers that are well-matched to the game used for evolution and, in some cases, also generalise well to previously unseen mazes. For comparison purposes, we also designed a controller manually using the same function set as GP. GP was able to significantly outperform this hand-designed controller. The best evolved controllers are competitive with the best reactive controllers reported for this problem.
Keywords :
computer games; genetic algorithms; learning (artificial intelligence); software agents; Ms PacMan game; genetic programming; reactive agents; Artificial intelligence; Artificial neural networks; Games; Genetic programming; Humans; Safety; Testing; Evolving Controllers; Genetic Programming; Pac-Man;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence (UKCI), 2010 UK Workshop on
Conference_Location :
Colchester
Print_ISBN :
978-1-4244-8774-5
Electronic_ISBN :
978-1-4244-8773-8
Type :
conf
DOI :
10.1109/UKCI.2010.5625586
Filename :
5625586
Link To Document :
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