Pareto evolution and co-evolution in cognitive neural agents synthesis for Tic-Tac-Toe

Yi, Jack Yau and Teo, Jason Tze Wi and Patricia Anthony, (2007) Pareto evolution and co-evolution in cognitive neural agents synthesis for Tic-Tac-Toe. In: IEEE Symposium on Computational Intelligence and Games, CIG 2007, 1-5 April 2007 , Honolulu, Hawaii.

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Official URL: http://dx.doi.org/10.1109/CIG.2007.368113

Abstract

Although a number of multi-objective evolutionary algorithms (MOEAs) have been proposed over the last two decades, very few studies have utilized MOEAs for game agent synthesis. Recently, we have suggested a co-evolutionary implementation using the Pareto evolutionary programming (PEP) algorithm. This paper describes a series of experiments using PEP for evolving artificial neural networks (ANNs) that act as game-playing agents. Three systems are compared: (i) a canonical PEP system, (ii) a co-evolving PEP system (PCEP) with 3 different setups, and (iii) a co-evolving PEP system that uses an archive (PCEP-A) with 3 different setups. The aim of this study is to provide insights on the effects of including co-evolutionary techniques on a MOEA by investigating and comparing these 3 different approaches in evolving intelligent agents as both first and second players in a deterministic zero-sum board game. The results indicate that the canonical PEP system outperformed both co-evolutionary PEP systems as it was able to evolve ANN agents with higher quality game-playing performance as both first and second game players. Hence, this study shows that a canonical MOEA without co-evolution is desirable for the synthesis of cognitive game AI agents

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:PCEP-A system , Pareto evolution , Pareto evolutionary programming , Tic-Tac-Toe , Artificial neural network , Canonical PEP system , Coevolutionary implementation , Coevolving PEP system , Cognitive game AI agents , Cognitive neural agents synthesis , Deterministic zero-sum board game , Game agent synthesis , Game-playing agents , Intelligent agents , Multiobjective evolutionary algorithm
Subjects:?? QA75.5-76.95 ??
Divisions:SCHOOL > School of Engineering and Information Technology
ID Code:1858
Deposited By:IR Admin
Deposited On:25 Feb 2011 10:07
Last Modified:30 Dec 2014 15:00

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