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
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.
DOI
10.1007/978-3-642-35101-3_29
Access Rights
free_to_read
Comments
This is an Author's Accepted Manuscript of: 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. The final publication is available at link.springer.com here