哈尔滨工业大学学报(英文版)
哈爾濱工業大學學報(英文版)
합이빈공업대학학보(영문판)
JOURNAL OF HARBIN INSTITUTE OF TECHNOLOGY
2004年
5期
564-568
,共5页
reinforcement learning%multi-agent%behavior%eligibility trace
The application of reinforcement learning is widely used by multi-agent systems in recent years. An agent uses a multi-agent system to cooperate with other agents to accomplish the given task, and one agent's be-havior usually affects the others' behaviors. In traditional reinforcement learning, one agent takes the others lo-cation, so it is difficult to consider the others' behavior, which decreases the learning efficiency. This paper proposes multi-agent reinforcement learning with cooperation based on eligibility traces, i.e. one agent esti-mates the other agent's behavior with the other agent's eligibility traces. The results of this simulation prove the validity of the proposed learning method.
