Multi-robot cooperation based on hierarchical reinforcement learning

被引：0

作者：

Cheng, Xiaobei ^{[1
]}

Shen, Jing ^{[1
]}

Liu, Haibo ^{[1
]}

Gu, Guochang ^{[1
]}

机构：

[1] Harbin Engn Univ, Coll Comp Sci & Technol, Harbin 150001, Peoples R China

来源：

COMPUTATIONAL SCIENCE - ICCS 2007, PT 3, PROCEEDINGS | 2007年 / 4489卷

关键词：

multi-robot; cooperation; hierarchical reinforcement learning;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：90 / +

页数：2

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