关键词: R学习, 合同网, 多Agent合作, 实时调度

Abstract: This paper proposes a real-time scheduling model based on contract net protocol structure employing reinforcement learning agents. To this end, an R-learning procedure is elaborated and embedded in machine agents’ decision process, enabling them to treat bid-invitations in more complicated way than in a simple contract net protocol environment. Efficiency of the proposed method is verified through experiments in a simulated real-time scheduling environment. Furthermore, the performance of mixed machine groups which comprises both reinforcement learning agents and non-reinforcement-learning agents shows that there is spontaneous implicit teamwork occurring between reinforcement learning agents, and this teamwork guarantees high quality output of the scheduling model.

Key words: R-learning, contract net protocol, multi-agent cooperation, real-time schedule