Control of Learning Types for Efficient Resource Allocation
نویسندگان
چکیده
This paper proposes an indirect control method by operating the kind of information given to users and changing their learning types, for efficient resource allocation. We constructed three types of agents, which are different in efficiency and accuracy of learning. First, they were compared using acquired payoff in a minority game, which is a simplified model of resource allocation problems. As a result, there were 4 distinct areas according to the two conditions, memory length and learning speed of the others’ model. Next, our control method was tested in these 4 areas. As a result, the number of the agents who use each resource was stabilized and all agents' average profit increased by this control method. Contact: Dr. Kiyoshi Izumi Cyber Assist Research Center, AIST 2-41-6 Aomi, Koto, Tokyo 135-0064, JAPAN Tel: 81-3-3599-8298 Fax: 81-3-5530-2067 Email: [email protected]
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