The evolution of cooperation in spatial prisoner’s dilemma game with dynamic relationship-based preferential learning

Abstract

The relationships in human society are heterogeneous and dynamically change with interactions, which have a strong effect on individual’s learning behaviors. In this light we present a new mechanism of preferential learning based on dynamic relationship into evolutionary spatial prisoner’s dilemma game to further investigate the incentive mechanisms of cooperative behaviors. In detail, we consider that the strength of relationship between pairwise individuals adaptively changes according to their mutual strategies and the adjusting rate is related to individuals’ sensitivity to interactions. Based on the heterogeneous and dynamic relationship, individuals prefer neighbors with stronger relationship to learn from instead of learning randomly The learning preference is measured by the preference intensity. By means of Monte Carlo simulations, we find that both the sensitivity factor and the preference intensity have multiple effects on the evolution of cooperation. Furthermore, to validate the multiple effects in a microcosmic view, strategy transitions during the evolution are also discussed. Interestingly, we find that there exists a trade-off between the influence of the sensitivity factor and the preference intensity on the evolution of cooperation. Presented results are robust to variations of the network structures and may provide a new understanding to the emergence of cooperative behaviors.