Abstract
We propose a game model that integrates reinforcement learning (RL) with link strategies and conformity behavior to investigate the emergence and maintenance of cooperation. The model operates on a lattice network with periodic boundaries and includes two types of nodes: RL nodes with link strategies and conformist nodes. Simulation results reveal a range of critical mass. Within this range, the interaction between these two types of nodes exhibits a nonlinear response between the cooperation rate and the temptation to betray, resulting in the phenomena of resonance-like cooperation and resonance-like defection, showing a nonlinear response between the cooperation rate and the temptation to betray. This study reveals the complex interactions between the two strategies as well as their influence on system behavior through numerical simulations and analysis. Our results provide fresh insights into understanding and promoting cooperative behavior between artificial intelligence and humans.
Published Version
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