Title :
Coevolving intelligent game players in a cultural framework
Author :
Sharma, Shiven ; Kobti, Ziad ; Goodwin, Scott G.
Author_Institution :
Sch. of Comput. Sci., Univ. of Windsor, Windsor, ON
Abstract :
Game playing has always provided an exciting avenue of research in Artificial Intelligence. Various methodologies and techniques have been developed to build intelligent game players. Coevolution has proven to be successful in learning how to play games with no prior game knowledge. In this paper we develop a coevolutionary system for the General Game Playing framework, where absolutely nothing is known about the game beforehand, and enhance it using Cultural Algorithms. In order to test the effectiveness of complementing coevolution with cultural algorithms, we play matches in several games between our player, a random player and one trained using standard coevolution.
Keywords :
artificial intelligence; evolutionary computation; game theory; artificial intelligence; coevolutionary system; coevolving intelligent game players; cultural algorithm; cultural framework; general game playing; random player; Artificial intelligence; Artificial neural networks; Computer science; Cultural differences; Feedforward neural networks; Feedforward systems; Intelligent agent; Learning; Neural networks; Testing;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983005