Abstract
AbstractUnder complex, dynamic and uncertain environment, tasks in multi-agent system need to be distributed to agents dynamically and agents need to cooperate to complete tasks assigned dynamically. This paper proposes a dynamic task allocation model based on game theory and dynamic coordination in task execution based on coordination graph at each time step. The synthesized model is solved by reinforcement learning. The detailed algorithm is illustrated with an example and experimental results show that the method is an effective solution for dynamic task allocation and execution coordination under uncertain environment.Keywordstask allocationcoordination graphQ-learninggame theory
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