A strategy with novel evolutionary features for the iterated prisoner's dilemma

Jiawei Li, Graham Kendall

Research output: Journal PublicationArticlepeer-review

16 Citations (Scopus)

Abstract

In recent iterated prisoner's dilemma tournaments, the most successful strategies were those that had identification mechanisms. By playing a predetermined sequence of moves and learning from their opponents' responses, these strategies managed to identify their opponents. We believe that these identification mechanisms may be very useful in evolutionary games. In this paper one such strategy, which we call collective strategy, is analyzed. Collective strategies apply a simple but efficient identification mechanism (that just distinguishes themselves from other strategies), and this mechanism allows them to only cooperate with their group members and defect against any others. In this way, collective strategies are able to maintain a stable population in evolutionary iterated prisoner's dilemma. By means of an invasion barrier, this strategy is compared with other strategies in evolutionary dynamics in order to demonstrate its evolutionary features. We also find that this collective behavior assists the evolution of cooperation in specific evolutionary environments.

Original languageEnglish
Pages (from-to)257-274
Number of pages18
JournalEvolutionary Computation
Volume17
Issue number2
DOIs
Publication statusPublished - Jun 2009
Externally publishedYes

Keywords

  • Evolutionarily stable
  • Identification mechanism
  • Invasion barrier
  • Iterated prisoner's dilemma

ASJC Scopus subject areas

  • Computational Mathematics

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