Determination of the optimal values of parameters in reinforcement learning for mobile robot navigation by a genetic algorithm

被引：1
|
作者：
Kamei, K [1 ]
Ishikawa, M [1 ]
机构：
[1] Kyushu Inst Technol, Grad Sch Life Sci & Syst Engn, Dept Brain Sci & Engn, Kitakyushu, Fukuoka 8080916, Japan
来源：
BRAIN-INSPIRED IT I | 2004年 / 1269卷
关键词：
genetic algorithm; reinforcement learning; mobile robot; navigation;
D O I：
10.1016/j.ics.2004.05.133
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Reinforcement learning is useful in location estimation, obstacle avoidance and path planning for autonomous mobile robots. We have to determine various parameters in reinforcement learning without prior information. We propose to determine the optimal values of parameters with the help of a genetic algorithm. We have succeeded in accelerating the speed of learning by about 20-30% and in decreasing the number of actions needed to reach the goal by about a half. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码：193 / 196
页数：4
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