A Strategy Adaptive Evolution Approach Based on the Public Goods Game

Cluster behavior is prevalent in nature. Many individuals change their to adapt a dynamically changing environment by following simple rules of and interacting with information from neighboring individuals. In this study, the traditional public goods game model improved combining advantages theory interactive learning. A strategy adaptive evolution method based on proposed. The emergence cooperative weighted networks under co-evolution strategies node weights explored conjunction multi-agent results show that strategic adaptation, person’s influence becomes greater if level adaptation exceeds desired level, less otherwise. This weight adjustment defined intensity parameter δ. moderate δ value can effectively facilitate occurrence evolution. cooperation depends mainly distribution participants, which leads formation clusters controlled high-weighted cooperators. Even great temptation defect, these cooperators prevail over defectors. increases heterogeneity research provides viable pathway solve social dilemmas will further promote application intelligent decision making.