Environmental information perception enhances cooperation in stochastic public goods games via Q-learning

Cooperation is the foundation of social progress, but due to rational individuals often prioritize personal interests, reciprocal cooperation is undermined. The Public Goods Game (PGG) is a classic model for studying group interactions. Traditional PGG assumes a static environment, but in reality, the environment is dynamically changing, and there is an interaction between individual behavior and the environment. Therefore, the stochastic game framework is proposed and applied to study the feedback mechanisms between behavior and the environment. This paper takes the two-state environmental transition mechanism as an example to explore the impact of environmental information perception ability on individual decision-making in the stochastic PGG. Specifically, we use the Q-learning algorithm to depict individual decision-making behavior and consider two types of individuals with different perception abilities: individuals with environmental perception ability select the best action based on the current environmental state, while individuals without environmental perception ability make decisions based solely on historical experience. The experimental results show that environmental information perception significantly lowers the cooperation threshold in the stochastic PGG. By analyzing the microscopic interaction modes of individuals, we find that there is an isolation zone effect between different strategy populations, which effectively prevents the erosion of defection behaviors and ensures the internal stability of cooperation. The extended experiments further validate the robustness of the results. This study shows that environmental information is beneficial for promoting the evolution of cooperation. These findings provide new insights into the cooperation mechanisms in stochastic PGG and offer valuable guidance for promoting cooperation in real-world societies.