A review of evolutionary graph theory with applications to game theory

Paulo Shakarian, Patrick Roos, Anthony Johnson

Research output: Contribution to journalReview article

89 Scopus citations

Abstract

Evolutionary graph theory (EGT), studies the ability of a mutant gene to overtake a finite structured population. In this review, we describe the original framework for EGT and the major work that has followed it. This review looks at the calculation of the " fixation probability" - the probability of a mutant taking over a population and focuses on game-theoretic applications. We look at varying topics such as alternate evolutionary dynamics, time to fixation, special topological cases, and game theoretic results. Throughout the review, we examine several interesting open problems that warrant further research.

Original languageEnglish (US)
Pages (from-to)66-80
Number of pages15
JournalBioSystems
Volume107
Issue number2
DOIs
StatePublished - Feb 1 2012
Externally publishedYes

Keywords

  • Evolutionary dynamics
  • Fixation probability
  • Game theory
  • Structured populations
  • Time to fixation

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology(all)
  • Applied Mathematics

Fingerprint Dive into the research topics of 'A review of evolutionary graph theory with applications to game theory'. Together they form a unique fingerprint.

Cite this