An evolutionary study on cooperation in N-person iterated prisoner’s dilemma game

Yeon Gyu Seo, Sung Bae Cho

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

1 Citation (Scopus)

Abstract

The iterated prisoner's dilemma game has been used to study on the evolution of cooperation in social, economic and biological systems. There have been much work on the relationship of number of players and cooperation, evolutionary strategy learning as a kind of machine learning, and the effect of payoff function to cooperation. This paper attempts to reveal that cooperative coalition size depends on payoff function and localization affects the evolution of cooperation in the N-player Iterated Prisoner's Dilemma (NIPD). Localization makes individuals to interact or learn with adjacent individuals. Experimental result reports that cooperative coalition size increases as the gradient of the payoff function for cooperation becomes steeper than that of defector's payoff function or as minimum coalition size gets smaller. It is also shown that localization of interaction is an important factor to affect cooperative coalition.

Original languageEnglish
Title of host publicationSimulated Evolution and Learning - 2nd Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1998, Selected Papers
EditorsBob McKay, Xin Yao, Charles S. Newton, Jong-Hwan Kim, Takeshi Furuhashi
PublisherSpringer Verlag
Pages301-308
Number of pages8
ISBN (Print)3540659072, 9783540659075
DOIs
Publication statusPublished - 1999
Event2nd Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1998 - Canberra, Australia
Duration: 1998 Nov 241998 Nov 27

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1585
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1998
CountryAustralia
CityCanberra
Period98/11/2498/11/27

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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