Evolutionary Dynamics of Variable Games in Structured Populations

Fuente: arXiv
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Main Authors: Pi, Bin, Feng, Minyu, Deng, Liang-Jian, Chen, Xiaojie, Szolnoki, Attila
Format: Preprint
Published: 2026
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_version_ 1866917355536252928
author Pi, Bin
Feng, Minyu
Deng, Liang-Jian
Chen, Xiaojie
Szolnoki, Attila
author_facet Pi, Bin
Feng, Minyu
Deng, Liang-Jian
Chen, Xiaojie
Szolnoki, Attila
contents The game interactions among individuals in nature are often uncertain and dynamically evolving, significantly influencing the persistence of cooperation. However, it remains a formidable challenge to effectively characterize these dynamic properties in structured populations, derive theoretical conditions for cooperation, and identify the optimal game distribution for promoting cooperation. To address these issues, we propose the variable game framework in a structured population, where the game interactions between different individuals change over time. By means of the Markov chain and the pair approximation method, we derive theoretical conditions under which cooperation is favored by natural selection and when it is favored over defection under weak selection. Furthermore, we respectively formulate and solve two optimization problems to determine the optimal game distribution that most effectively fosters the evolution of cooperation by maximizing the gradient of cooperation selection and minimizing the fitness difference between defectors and cooperators. The theoretical predictions regarding both the conditions for cooperation and optimal game distribution are further validated by numerical calculations and extensive Monte Carlo simulations. Our findings offer novel insights into the mechanisms driving cooperative behavior in complex systems and provide theoretical guidance for designing optimal game environments that facilitate the evolution of cooperation.
format Preprint
id arxiv_https___arxiv_org_abs_2603_20603
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Evolutionary Dynamics of Variable Games in Structured Populations
Pi, Bin
Feng, Minyu
Deng, Liang-Jian
Chen, Xiaojie
Szolnoki, Attila
Computer Science and Game Theory
Social and Information Networks
The game interactions among individuals in nature are often uncertain and dynamically evolving, significantly influencing the persistence of cooperation. However, it remains a formidable challenge to effectively characterize these dynamic properties in structured populations, derive theoretical conditions for cooperation, and identify the optimal game distribution for promoting cooperation. To address these issues, we propose the variable game framework in a structured population, where the game interactions between different individuals change over time. By means of the Markov chain and the pair approximation method, we derive theoretical conditions under which cooperation is favored by natural selection and when it is favored over defection under weak selection. Furthermore, we respectively formulate and solve two optimization problems to determine the optimal game distribution that most effectively fosters the evolution of cooperation by maximizing the gradient of cooperation selection and minimizing the fitness difference between defectors and cooperators. The theoretical predictions regarding both the conditions for cooperation and optimal game distribution are further validated by numerical calculations and extensive Monte Carlo simulations. Our findings offer novel insights into the mechanisms driving cooperative behavior in complex systems and provide theoretical guidance for designing optimal game environments that facilitate the evolution of cooperation.
title Evolutionary Dynamics of Variable Games in Structured Populations
topic Computer Science and Game Theory
Social and Information Networks
url https://arxiv.org/abs/2603.20603