A Tournament-Based Competitive Coevolutionary Algorithm

  • Authors:
  • Yeo Keun Kim;Jae Yun Kim;Yeongho Kim

  • Affiliations:
  • Department of Industrial Engineering, Chonnam National University, Gwangju, 500-757, Republic of Korea. kimyk@chonnam.ac.kr;Department of Industrial Engineering, Chonnam National University, Gwangju, 500-757, Republic of Korea. ieman@chonnam.ac.kr;Department of Industrial Engineering and Research Institute of Engineering Science, Seoul National University, Seoul, 151-742, Republic of Korea. yeongho@snu.ac.kr

  • Venue:
  • Applied Intelligence
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

For an efficient competitive coevolutionary algorithm, it is important that competing populations be capable of maintaining a coevolutionary balance and hence, continuing evolutionary arms race to increase the levels of complexity. We propose a competitive coevolutionary algorithm that combines the strategies of neighborhood-based evolution, entry fee exchange tournament competition (EFE-TC) and localized elitism. An emphasis is placed on analyzing the effects of these strategies on the performance of competitive coevolutionary algorithms. We have tested the proposed algorithm with two adversarial problems: sorting network and Nim game problems that have different characteristics. The experimental results show that the interacting effects of the strategies appear to promote a balanced evolution between host and parasite populations, which naturally leads them to keep on evolutionary arms race. Consequently, the proposed algorithm provides good quality solutions with a little computation time.