Multi-robot Cooperation Based on Hierarchical Reinforcement Learning

Authors:
Xiaobei Cheng;Jing Shen;Haibo Liu;Guochang Gu
Affiliations:
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China;College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China;College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China;College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Year:
2007

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Abstract

Multi-agent reinforcement learning for multi-robot systems is a challenging issue in both robotics and artificial intelligence. But multi-agent reinforcement learning is bedeviled by the curse of dimensionality. In this paper, a novel hierarchical reinforcement learning approach named MOMQ is presented for multi-robot cooperation. The performance of MOMQ is demonstrated in three-robot trash collection task.