Multagent Control Strategy Using Reinforcement Learning 


Vol. 10,  No. 3, pp. 249-256, Jun.  2003
10.3745/KIPSTB.2003.10.3.249


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  Abstract

The most important problems in the multi-agent system are to accomplish a goal through the efficient coordination of several agents and to prevent collision with other agents. In this paper, we propose a new control strategy for succeeding the goal of the prey pursuit problem efficiently. Our control method uses reinforcement learning to control the multi-agent system and consider the distance as well as the space relationship between the agents in the state space of the prey pursuit problem.

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[IEEE Style]

H. I. Lee and B. C. Kim, "Multagent Control Strategy Using Reinforcement Learning," The KIPS Transactions:PartB , vol. 10, no. 3, pp. 249-256, 2003. DOI: 10.3745/KIPSTB.2003.10.3.249.

[ACM Style]

Hyong Ill Lee and Byung Cheon Kim. 2003. Multagent Control Strategy Using Reinforcement Learning. The KIPS Transactions:PartB , 10, 3, (2003), 249-256. DOI: 10.3745/KIPSTB.2003.10.3.249.

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