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Expertness measuring in cooperative learning

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4 Author(s)
Ahmadabadi, M.N. ; Robotics Lab., Tehran Univ., Iran ; Asadpur, M. ; Khodanbakhsh, S.H. ; Nakano, E.

Cooperative learning in a multi-agent system can improve the learning quality and learning speed. The improvement can be gained if each agent detects the expert agents and uses their knowledge properly. In the paper, a cooperative learning method, called weighted strategy sharing (WSS) is introduced. Also some criteria are introduced to measure the expertness of agents. In WSS, based on the amount of its team-mate expertness, each agent assigns a weight to their knowledge. These weights are used in sharing knowledge among agents in our system. WSS and the expertness criteria are tested on two simulated hunter-prey problems and on object pushing systems

Published in:

Intelligent Robots and Systems, 2000. (IROS 2000). Proceedings. 2000 IEEE/RSJ International Conference on  (Volume:3 )

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