Finite automata play repeated prisoner's dilemma with information processing costs

Teck Hua Ho*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

28 Citations (Scopus)

Abstract

We study the finitely repeated Prisoner's Dilemma game. Our players are modeled as finite automata. A population of boundedly rational players compete in a 'survival of the fittest' evolution contest simulated using Holland's genetic algorithm. Starting from a hostile population which plays defection frequently, our simulation results show that players converge to play cooperatively. This emergence of cooperative behavior breaks down when we penalize a complex strategy based on the size of the machine. On the other hand, a penalty cost that increases with the frequency an automaton switches states will not hurt the development of cooperative behavior.

Original languageEnglish
Pages (from-to)173-207
Number of pages35
JournalJournal of Economic Dynamics and Control
Volume20
Issue number1-3
DOIs
Publication statusPublished - 1996
Externally publishedYes

ASJC Scopus Subject Areas

  • Economics and Econometrics
  • Control and Optimization
  • Applied Mathematics

Keywords

  • Computational complexity
  • Genetic algorithm
  • Learning
  • Prisoner's dilemma

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