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Genetic Algorithm for Repeated Prisoner’s Dilemma Научная публикация

Конференция

XXIV International conference “Mathematical Optimization Theory and Operations Research”
07-11 июл. 2025 , Новосибирск

Сборник

Mathematical Optimization Theory and Operations Research : 24th International Conference, MOTOR 2025, Novosibirsk, Russia, July 7–11, 2025, Proceedings
Сборник, Springer Nature. Switzerland.2025. 405 c. ISBN 978-3-031-97077-1.

Журнал

Lecture Notes in Computer Science
ISSN: 0302-9743 , E-ISSN: 1611-3349

Вых. Данные

Год: 2025, Том: 15681, Страницы: 208-218 Страниц : 11 DOI: 10.1007/978-3-031-97077-1_15

Ключевые слова

Prisoner’s dilemma, Strategies, Evolution of strategies, Survivability of strategies

Авторы

Gruzdev Nikita A. ^1,2

Организации

1	Sobolev Institute of Mathematics
2	Dostoevsky Omsk State University

Информация о финансировании (1)

Российский научный фонд

25-21-00335

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

Gruzdev N.A.
Genetic Algorithm for Repeated Prisoner’s Dilemma
В сборнике 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

Опубликована в печати:	7 авг. 2025 г.
Опубликована online:	7 авг. 2025 г.

≡ Scopus:	2-s2.0-105010833475
≡ OpenAlex:	W4412044090