Promoting cooperation in multi agent systems through fuzzy social plasticity

In multi agent systems, agents are supposed to be aware of each other and need to cooperate with their neighboring agents in order to reach their objectives. However, there may be some selfish agents that reject cooperation due to the cost of performing the requested task, even while taking benefit from network resources and using intermediate agents to send their requests. The existence of these nodes cannot be ignored; and system efficiency can significantly deteriorate as the number of such nodes increases. Thus, a special mechanism is needed in order to confront them. Here, local structural update based on fuzzy social plasticity is proposed to persuade cooperative behavior. In this mechanism, relationships with non-cooperative agents are disconnected and the more cooperative ones, i.e. those with a trusting history for cooperation, and closer agents are preferred for the chain of relationship by a fuzzy logic heuristic. The proposed strategy intensifies cooperation by diminishing the impact of non-cooperation and reinforcing that of the cooperation. The strategy is evaluated on some random networks with different cooperation rates. Results confirm increased network cooperation, even when the majority of the agents are non-cooperative.