The coupling effect between the environment and strategies drives the emergence of group cooperation
Changyan Di, Qingguo Zhou, Jun Shen, Jinqiang Wang, Rui Zhou, Tianyi, Wang

TL;DR
This paper introduces a multi-agent reinforcement learning model to study how the interaction between environment and strategies fosters group cooperation in finite populations, revealing the importance of environmental feedback in cooperation dynamics.
Contribution
It presents a novel bottom-up computational approach to analyze eco-evolutionary dynamics, emphasizing the role of environmental feedback in the emergence of cooperation.
Findings
High cooperation levels can emerge even in defector-favoring environments.
Environmental degradation can diminish defection benefits, promoting cooperation.
Agents detect environmental inflection points through rewards, triggering cooperation.
Abstract
Introducing environmental feedback into evolutionary game theory has led to the development of eco-evolutionary games, which have gained popularity due to their ability to capture the intricate interplay between the environment and decision-making processes. However, current researches in this field focus on the study to macroscopic evolutionary dynamics in infinite populations. In this study, we propose a multi-agent computational model based on reinforcement learning to explore the coupled dynamics between strategies and the environment in finite populations from a bottom-up perspective. Our findings indicate that even in environments that favor defectors, high levels of group cooperation can emerge from self-interested individuals, highlighting the significant role of the coupling effect between the environment and strategies. Over time, the higher payoff of defection can be diluted…
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Taxonomy
TopicsEvolutionary Game Theory and Cooperation · Evolution and Genetic Dynamics · Experimental Behavioral Economics Studies
