A New Game Model of Task Forwarding for a Multiagent System Based on a Reputation Mechanism

Promoting the efficiency of task forwarding is a key issue in search and rescue operations, aerospace applications and so on. In this brief, we introduce a reputation mechanism existing in an evolutionary game into the task forwarding process of a multiagent system to promote the cooperation rate between agents. Combining the reputation mechanism with strategy updating of a multiagent system, a model based on evolutionary game theory is built and tested, and key factors such as the reputation threshold and the percentage of agents who initially select the forwarding strategy are analyzed in this brief. A numerical simulation shows that compared with previous studies, the model in this brief can make the proportion of agents choosing the forwarding strategy in a multiagent system reach a steady state faster. Through an analysis of various parameters, we also make this new model applicable to more realistic situations, which provides a more appropriate method for task forwarding in multiagent systems.