Information fusion based on reputation and payoff promotes cooperation in spatial public goods game

Abstract Reputation information plays an important role in human behavioral interactions. There have been many studies that have considered reputation in spatial public goods game models, but they essentially assumed that reputation will only change the payoff structure of the game (individuals with a good reputation will get more benefits in the future). In fact, individuals with good reputation will have greater influences which can also affect the decision of neighbors around them in the strategy updating process. Grounded on this observation, we proposed an improved strategy learning rule considering both reputation and payoff information. We employ evidence theory to fuse these two aspects of information, based on which individual strategies can be updated. In addition, we construct a weight coefficient to quantify the importance and reliability of reputation. Through numerical simulations, it is unraveled that the reputation effect can greatly attract nearest neighbors to form greater clusters, thus promoting the emergence of cooperation. With the reputation weight increasing gradually, the critical enhancement factor for cooperation to arise is by degrees reduced to the lower boundary, demonstrating that an increasing tendency of strategy adoption relying on reputation is more likely to allow cooperation to thrive. In the region of low reputation weights, reputation only plays a subtle role in inducing cooperation. Within the region of high reputation weights, cooperation is dramatically boosted by reputation and cooperators can swiftly occupy the whole population. Our work may be helpful to further understand the effect of reputation on the emergence of cooperation.