The coevolution of cooperation: Integrating Q-learning and occasional social interactions in evolutionary games

This study explores the emergence and maintenance of cooperation in evolutionary game theory by incorporating occasional social interactions into Q-learning algorithms. We model the dynamics on a square lattice, where individuals play the Prisoner’s Dilemma Game and update their strategies based on Q-learning and infrequent social interactions. Our main findings reveal a non-monotonic relationship between the game parameter $c$ and cooperation levels, with cooperation re-emerging in adverse conditions. The interplay between Q-learning and social learning mechanisms is key, with social learning playing a more significant role in sustaining cooperation under challenging conditions. This work advances our understanding of cooperation maintenance in populations and has implications for designing strategies to foster cooperation in real-world scenarios.