Learning and evolution affected by spatial structure

Masahiro Ono, Mitsuru Ishizuka

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

4 Citations (Scopus)

Abstract

In this study, we explore the roles of learning and evolution in a non-cooperative autonomous system through a spatial IPD (Iterated Prisoner's Dilemma) game. First, we propose a new agent model playing the IPD game; the game has a gene of the coded parameters of reinforcement learning. The agents evolve and learn during the course of the game. Second, we report an empirical study. In our simulation, we observe that the spatial structure affects learning and evolution. Learning is not effective for achieving mutual cooperation except under certain special conditions. The learning process depends on the spatial structure.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages651-660
Number of pages10
Volume4099 LNAI
Publication statusPublished - 2006
Externally publishedYes
Event9th Pacific Rim International Conference on Artificial Intelligence - Guilin
Duration: 2006 Aug 72006 Aug 11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4099 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other9th Pacific Rim International Conference on Artificial Intelligence
CityGuilin
Period06/8/706/8/11

Keywords

  • Game theory
  • Prisoner's dilemma
  • Small world network

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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  • Cite this

    Ono, M., & Ishizuka, M. (2006). Learning and evolution affected by spatial structure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4099 LNAI, pp. 651-660). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4099 LNAI).