Multi-Task Coalition Parallel Formation Strategy Based on Reinforcement Learning
نویسندگان
چکیده
Agent coalition is an important manner of agents’ coordination and cooperation. Forming a coalition, agents can enhance their ability to solve problems and obtain more utility. In this paper, a novel multi-task coalition parallel formation strategy is presented, and the conclusion that the process of multi-task coalition formation is a Markov Decision Process is testified theoretically. Moreover, reinforcement learning is used to solve agents’ behavior strategy, and the process of multi-task coalition parallel formation is described. In multi-task oriented domains, the strategy can effectively and parallel reach multi-task coalitions.
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