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A hybird approach to multi-agent pursuit-evasion game

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4 Author(s)
Jong-Yin Kuo ; Dept. of Comput. Sci. & Inf. Eng., Nat. Taipei Univ. of Technol., Taipei, Taiwan ; Yong-Yi FanJiang ; Shang-Pin Ma ; Jia-Lin Syu

In multi-agent pursuit-evasion game, pursuers need to coordinate the behavior of each other to achieve a common goal: catching the evader. In this paper, a learning mechanism to capture evader in a dynamic environment of pursuit-evasion game is proposed. It deals with the uncertainty in environment using training and, according to whether the agents cooperated with each other, agent learning is divided into two ways: one is individual learning and the other is case-based reasoning. With these methods, agents are capable of memorizing and learning in order to catch evader more quickly.

Published in:

Machine Learning and Cybernetics (ICMLC), 2011 International Conference on  (Volume:1 )

Date of Conference:

10-13 July 2011