Sciact
  • EN
  • RU

Genetic Algorithm for Repeated Prisoner’s Dilemma Full article

Conference XXIV International conference “Mathematical Optimization Theory and Operations Research”
07-11 Jul 2025 , Новосибирск
Source Mathematical Optimization Theory and Operations Research : 24th International Conference, MOTOR 2025, Novosibirsk, Russia, July 7–11, 2025, Proceedings
Compilation, Springer Nature. Switzerland.2025. 405 c. ISBN 978-3-031-97077-1.
Journal Lecture Notes in Computer Science
ISSN: 0302-9743 , E-ISSN: 1611-3349
Output data Year: 2025, Volume: 15681, Pages: 208-218 Pages count : 11 DOI: 10.1007/978-3-031-97077-1_15
Tags Prisoner’s dilemma, Strategies, Evolution of strategies, Survivability of strategies
Authors Gruzdev Nikita A. 1,2
Affiliations
1 Sobolev Institute of Mathematics
2 Dostoevsky Omsk State University

Funding (1)

1 Russian Science Foundation 25-21-00335

Abstract: The paper deals with the repeated prisoner’s dilemma and evolving strategies for this game. For evolving strategies, an algorithm has been developed that simulates the evolution of strategies in an iterated prisoner’s dilemma, using selection, mutation and crossover operators. A new crossover operator has been developed to maximize the total population gain in the repeated prisoner’s dilemma
Cite: Gruzdev N.A.
Genetic Algorithm for Repeated Prisoner’s Dilemma
In compilation Mathematical Optimization Theory and Operations Research : 24th International Conference, MOTOR 2025, Novosibirsk, Russia, July 7–11, 2025, Proceedings. – Springer Nature., 2025. – C.208-218. – ISBN 978-3-031-97077-1. DOI: 10.1007/978-3-031-97077-1_15 Scopus OpenAlex
Dates:
Published print: Aug 7, 2025
Published online: Aug 7, 2025
Identifiers:
≡ Scopus: 2-s2.0-105010833475
≡ OpenAlex: W4412044090
Altmetrics: