Evolutionary successful strategies in a transparent iterated prisoner’s dilemma

Anton M. Unakafov*, Thomas Schultze, Igor Kagan, Sebastian Moeller, Alexander Gail, Stefan Treue, Stephan Eule, Fred Wolf

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A Transparent game is a game-theoretic setting that takes action visibility into account. In each round, depending on the relative timing of their actions, players have a certain probability to see their partner’s choice before making their own decision. This probability is determined by the level of transparency. At the two extremes, a game with zero transparency is equivalent to the classical simultaneous game, and a game with maximal transparency corresponds to a sequential game. Despite the prevalence of intermediate transparency in many everyday interactions such scenarios have not been sufficiently studied. Here we consider a transparent iterated Prisoner’s dilemma (iPD) and use evolutionary simulations to investigate how and why the success of various strategies changes with the level of transparency. We demonstrate that non-zero transparency greatly reduces the set of successful memory-one strategies compared to the simultaneous iPD. For low and moderate transparency the classical “Win - Stay, Lose - Shift” (WSLS) strategy is the only evolutionary successful strategy. For high transparency all strategies are evolutionary unstable in the sense that they can be easily counteracted, and, finally, for maximal transparency a novel “Leader-Follower” strategy outperforms WSLS. Our results provide a partial explanation for the fact that the strategies proposed for the simultaneous iPD are rarely observed in nature, where high levels of transparency are common.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computation - 22nd International Conference, EvoApplications 2019, Held as Part of EvoStar 2019, Proceedings
EditorsPedro A. Castillo, Paul Kaufmann
PublisherSpringer Verlag
Pages204-219
Number of pages16
ISBN (Print)9783030166915
DOIs
Publication statusPublished - 30 Mar 2019
Externally publishedYes
Event22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held as Part of EvoStar 2019 - Leipzig, Germany
Duration: 24 Apr 201926 Apr 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11454 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Applications of Evolutionary Computation, EvoApplications 2019, held as Part of EvoStar 2019
Country/TerritoryGermany
CityLeipzig
Period24/04/201926/04/2019

Bibliographical note

Funding Information:
Acknowledgments. We acknowledge funding from the Ministry for Science and Education of Lower Saxony and the Volkswagen Foundation through the program “Niedersächsisches Vorab”. Additional support was provided by the Leibniz Association through funding for the Leibniz ScienceCampus Primate Cognition and the Max Planck Society.

Publisher Copyright:
© Springer Nature Switzerland AG 2019.

Keywords

  • Evolutionary game theory
  • iterated Prisoner’s Dilemma
  • Transparent games

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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