Dynamic noise from action errors enhances network reciprocity in the prisoner's dilemma game

Jun Tanimoto, Takashi Ogasawara

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Inspired by the fact that people make mistakes in a transient, fluctuating or chaotic environment, we establish a spatial prisoner's dilemma model where an agent commits action errors proportionally varying with the increasing/decreasing rate of the global cooperation fraction. A series of numerical simulations reveal that the cooperation level is enhanced in games in which the stag hunt (SH)-type dilemma is dominant; however, it is slightly diminished in games in which the chicken-type dilemma is dominant, compared with the standard network reciprocity model. Intensive analysis reveals that the noise created by the action error contribute to the spatial expansion of a cooperators' cluster, because a dilemma that is less chicken-type and more SH-type makes it disadvantageous for defectors to neighbor cooperators. Our finding, that errors in behavior in a chaotic environment contribute to the evolution of cooperation, might aim to explain the problem of how network reciprocity works.

Original languageEnglish
Article numberP01033
JournalJournal of Statistical Mechanics: Theory and Experiment
Volume2015
Issue number1
DOIs
Publication statusPublished - 2015

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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