Altruistic Behavior in Complex Network Based on Reputation and Future Expectation

According to game theory, the altruistic behavior on complex network is researched by a mechanism Based on reputation and future expectation we proposed. As the information of players´ historical behavior, reputation is an important foundation while players choose opponent. The players not only consider current payoff but also care about future payoff when they employ strategy. Simulations and analyses show players choose cooperation voluntarily for the purpose of payoff-maximizing. The level of convergence average reputation of group does not rely on the level of initial average reputation of group. The group can converge to full cooperation even though the initial average reputation of group is small. In a certain interval, a slight increase of the initial average reputation of group can effectively increase the level of cooperation of group. In addition, we found complex network has a certain ability to resist disturbance by simulating the non-subjective factors exist in the real world. Concentrating on the situation of group state changes from cooperative to defective, dynamic spatial patterns show shortcuts are the main reason of the emergence of new defective clusters under the mechanism.