Enhancing cooperation in dynamic networks through reinforcement-learning-based rewiring strategies
Cooperation is a fundamental aspect of social and biological systems, yet achieving and maintaining high levels of cooperation remains a significant challenge. This study investigates the dynamics of cooperation among players engaged in repeated two-player Prisoner’s Dilemma games, utilizing a novel...
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| Format: | Article |
| Language: | English |
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IOP Publishing
2025-01-01
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| Series: | New Journal of Physics |
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| Online Access: | https://doi.org/10.1088/1367-2630/adac87 |
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| author | Hsuan-Wei Lee Szu-Ping Chen Feng Shi |
| author_facet | Hsuan-Wei Lee Szu-Ping Chen Feng Shi |
| author_sort | Hsuan-Wei Lee |
| collection | DOAJ |
| description | Cooperation is a fundamental aspect of social and biological systems, yet achieving and maintaining high levels of cooperation remains a significant challenge. This study investigates the dynamics of cooperation among players engaged in repeated two-player Prisoner’s Dilemma games, utilizing a novel integration of the Bush–Mosteller reinforcement learning model with adaptive network rewiring mechanisms. Each player updates its probability of cooperation and rewires its connections based on the payoffs received from neighbors. Our results demonstrate that incorporating network rewiring guided by reinforcement learning significantly enhances both the level of cooperation and the average payoff across the population. Players that prioritize rewiring over strategy updates are found to form more stable cooperative structures, while those with heightened sensitivity to payoffs and optimal aspiration levels achieve greater cooperation. By identifying and analyzing key parameters that influence cooperative dynamics, our findings provide deep insights into the mechanisms that drive cooperative behavior. This research not only highlights the transformative potential of adaptive network rewiring in promoting cooperation within complex adaptive systems but also offers a framework for designing resilient cooperative networks across diverse domains. |
| format | Article |
| id | doaj-art-f8246fceaeca4bb68952b2f76dba3b17 |
| institution | Kabale University |
| issn | 1367-2630 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | New Journal of Physics |
| spelling | doaj-art-f8246fceaeca4bb68952b2f76dba3b172025-01-30T13:15:56ZengIOP PublishingNew Journal of Physics1367-26302025-01-0127101302510.1088/1367-2630/adac87Enhancing cooperation in dynamic networks through reinforcement-learning-based rewiring strategiesHsuan-Wei Lee0Szu-Ping Chen1Feng Shi2College of Health, Lehigh University , Bethlehem, PA, United States of AmericaPlant Breeding and Genetics section, School of Integrative Plant Science, Cornell University , Ithaca, NY, United States of AmericaIndependent Researcher , Seattle, WA, United States of AmericaCooperation is a fundamental aspect of social and biological systems, yet achieving and maintaining high levels of cooperation remains a significant challenge. This study investigates the dynamics of cooperation among players engaged in repeated two-player Prisoner’s Dilemma games, utilizing a novel integration of the Bush–Mosteller reinforcement learning model with adaptive network rewiring mechanisms. Each player updates its probability of cooperation and rewires its connections based on the payoffs received from neighbors. Our results demonstrate that incorporating network rewiring guided by reinforcement learning significantly enhances both the level of cooperation and the average payoff across the population. Players that prioritize rewiring over strategy updates are found to form more stable cooperative structures, while those with heightened sensitivity to payoffs and optimal aspiration levels achieve greater cooperation. By identifying and analyzing key parameters that influence cooperative dynamics, our findings provide deep insights into the mechanisms that drive cooperative behavior. This research not only highlights the transformative potential of adaptive network rewiring in promoting cooperation within complex adaptive systems but also offers a framework for designing resilient cooperative networks across diverse domains.https://doi.org/10.1088/1367-2630/adac87reinforcement learningPrisoner’s Dilemmacooperation dynamicsnetwork rewiringsocial networks |
| spellingShingle | Hsuan-Wei Lee Szu-Ping Chen Feng Shi Enhancing cooperation in dynamic networks through reinforcement-learning-based rewiring strategies New Journal of Physics reinforcement learning Prisoner’s Dilemma cooperation dynamics network rewiring social networks |
| title | Enhancing cooperation in dynamic networks through reinforcement-learning-based rewiring strategies |
| title_full | Enhancing cooperation in dynamic networks through reinforcement-learning-based rewiring strategies |
| title_fullStr | Enhancing cooperation in dynamic networks through reinforcement-learning-based rewiring strategies |
| title_full_unstemmed | Enhancing cooperation in dynamic networks through reinforcement-learning-based rewiring strategies |
| title_short | Enhancing cooperation in dynamic networks through reinforcement-learning-based rewiring strategies |
| title_sort | enhancing cooperation in dynamic networks through reinforcement learning based rewiring strategies |
| topic | reinforcement learning Prisoner’s Dilemma cooperation dynamics network rewiring social networks |
| url | https://doi.org/10.1088/1367-2630/adac87 |
| work_keys_str_mv | AT hsuanweilee enhancingcooperationindynamicnetworksthroughreinforcementlearningbasedrewiringstrategies AT szupingchen enhancingcooperationindynamicnetworksthroughreinforcementlearningbasedrewiringstrategies AT fengshi enhancingcooperationindynamicnetworksthroughreinforcementlearningbasedrewiringstrategies |