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

Jun Tanimoto, Takashi Ogasawara

Research output: Contribution to journalArticle

5 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

Fingerprint

Prisoner's Dilemma Game
Dilemma
games
Reciprocity
chickens
Game
Evolution of Cooperation
Prisoners' Dilemma
Numerical Simulation
expansion
Series
Model
Prisoner's dilemma game
simulation
Chicken

All Science Journal Classification (ASJC) codes

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

Cite this

Dynamic noise from action errors enhances network reciprocity in the prisoner's dilemma game. / Tanimoto, Jun; Ogasawara, Takashi.

In: Journal of Statistical Mechanics: Theory and Experiment, Vol. 2015, No. 1, P01033, 2015.

Research output: Contribution to journalArticle

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