The emergence of reactive strategies in simulated heterogeneous populations

Ilan Fischer

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

The computer simulation study explores the impact of the duration of social impact on the generation and stabilization of cooperative strategies. Rather than seeding the simulations with a finite set of strategies, a continuous distribution of strategies is being defined. Members of heterogeneous populations were characterized by a pair of probabilistic reactive strategies: the probability to respond to cooperation by cooperation and the probability to respond to defection by cooperation. This generalized reactive strategy yields the standard TFT mechanism, the All-Cooperate, All-Defect and Bully strategies as special cases. Pairs of strategies interacted through a Prisoner's Dilemma game and exerted social influence on all other members. Manipulating: (i) the initial distribution of populations' strategies, and (ii) the duration of social influence, we monitored the conditions leading to the emergence and stabilization of cooperative strategies. Results show that: (1) The duration of interactions between pairs of strategies constitutes a crucial factor for the emergence and stabilization of cooperative strategies, (2) Unless sufficient learning intervals are provided, initializing the simulations with cooperative populations does not guarantee that cooperation will sustain.

Original languageEnglish
Pages (from-to)289-314
Number of pages26
JournalTheory and Decision
Volume55
Issue number4
DOIs
StatePublished - 1 Dec 2003

Keywords

  • Computer simulation
  • Duration of interaction
  • Heterogeneous populations
  • Prisoner's Dilemma
  • Probabilistic Tit For Tat
  • Reactive strategies
  • Social impact

ASJC Scopus subject areas

  • General Decision Sciences
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Applied Psychology
  • General Social Sciences
  • General Economics, Econometrics and Finance
  • Computer Science Applications

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