Sustaining behavioral diversity in NEAT

Hirotaka Moriguchi, Shinichi Honiden

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Niching schemes, which sustains population diversity and let an evolutionary population avoid premature convergence, have been extensively studied in the research field of evolutionary algorithms. Neuroevolutionary (NE) algorithms, such as NEAT, have also benefitted from niching. However, the latest research indicates that the use of genotypeor phenotype-similarity-based niching schemes in NE algorithms is not highly effective because these schemes have difficulty sustaining the behavioral diversity in the environment. In this paper, we propose a novel niching scheme that takes into consideration both the phenotypic and behavioral diversity, and then integrate it with NEAT. An experimental analysis revealed that the proposed algorithm outperforms the original NEAT for various problem settings. More interestingly, it performs especially well for problems with a high noise level and large state space. Since these features are common in problems to which NEAT is applied, the proposed algorithm should be effective in practice.

Original languageEnglish
Title of host publicationProceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10
Pages611-618
Number of pages8
DOIs
Publication statusPublished - 2010 Aug 27
Event12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010 - Portland, OR, United States
Duration: 2010 Jul 72010 Jul 11

Publication series

NameProceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10

Conference

Conference12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010
CountryUnited States
CityPortland, OR
Period10/7/710/7/11

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Keywords

  • Behavioral diversity
  • NEAT
  • Neuroevolution
  • Niching
  • Premature convergence

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

Cite this

Moriguchi, H., & Honiden, S. (2010). Sustaining behavioral diversity in NEAT. In Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10 (pp. 611-618). (Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10). https://doi.org/10.1145/1830483.1830595