NDLI: Cooperative behavior acquisition in multi robots environment by reinforcement learning based on action selection level

Content Provider	IEEE Xplore Digital Library
Author	Hai-Tao Chu Bing-Rong Hong
Copyright Year	2000
Description	Author affiliation: Dept. of Comput. Sci., Harbin Inst. of Technol., China (Hai-Tao Chu)
Abstract	In a multi robots environment, the overlap of actions selected by each robot makes the acquisition of cooperation behaviors less efficient. So we propose an approach to determine the action selection priority level based on which the cooperative behaviors can be well controlled. First, we define eight levels for the action selection priority, which can be correspondingly mapped to eight subspaces of actions. Then by the local potential field method the action selection priority level for each robot is calculated and thus its action subspace is obtained. Third, reinforcement learning (RL) is employed to choose a proper action for each robot in its action subspace. Finally we have applied the proposed method to a soccer playing situation and the efficiency was verified by the results of both the computer simulation and real experiments.
Starting Page	1397
Ending Page	1402
File Size	586760
Page Count	6
File Format	PDF
ISBN	0780363485
DOI	10.1109/IROS.2000.893216
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-10-31
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robots Orbital robotics Computer science Computer simulation Learning systems Decision trees System identification
Content Type	Text
Resource Type	Article

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