Learning and evolution affected by spatial structure

Masahiro Ono, Mitsuru Ishizuka

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ページ651-660
ページ数10
4099 LNAI
出版ステータスPublished - 2006
外部発表はい
イベント9th Pacific Rim International Conference on Artificial Intelligence - Guilin
継続期間: 2006 8 72006 8 11

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4099 LNAI
ISSN(印刷版)03029743
ISSN(電子版)16113349

Other

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

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 生化学、遺伝学、分子生物学(全般)
  • 理論的コンピュータサイエンス

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