Document Type

Conference Proceeding

Publisher

Springer

Faculty

Faculty of Computing, Health and Science

School

School of Computer and Security Science / Artificial Intelligence and Optimisation Research Group

RAS ID

14846

Comments

This article was originally published as: Hingston, P. F., Ranjeet, T. R., Lam, C. P., & Masek, M. (2012). A Multimodal Problem for Competitive Coevolution. Proceedings of Australasian Joint Conference on Artificial Intelligence, AI 2012. (pp. 338-349). Sydney, Austraia. Springer. Original article available here

Abstract

Coevolutionary algorithms are a special kind of evolutionary algorithm with advantages in solving certain specific kinds of problems. In particular, competitive coevolutionary algorithms can be used to study problems in which two sides compete against each other and must choose a suitable strategy. Often these problems are multimodal - there is more than one strong strategy for each side. In this paper, we introduce a scalable multimodal test problem for competitive coevolution, and use it to investigate the effectiveness of some common coevolutionary algorithm enhancement techniques.

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