Title :
One fast RL algorithm and its application in mobile robot navigation
Author :
Duan, Yong ; Li, Chen ; Xie, MingChen
Author_Institution :
Shenyang Univ. of Technol., Shenyang, China
Abstract :
Reinforcement learning is a method for search optimal strategy on condition of unknown apriority knowledge. When the learning tasks are complex and work condition dynamically change, learning speed is too slow. For this problem, a kind of speedup reinforcement learning algorithm based on learning experience replay is proposed in this paper. Firstly, the experience sample database is built gradually in the learning process. Secondly, the efficiency of reinforcement learning is improved by experience samples replaying. Finally, the presented method is used to solve the problems of mobile robot navigation, the validity is testified.
Keywords :
learning (artificial intelligence); mobile robots; path planning; search problems; fast RL algorithm; learning experience; learning process; learning speed; mobile robot navigation; reinforcement learning; search optimal strategy; Databases; Learning; Mobile robots; Navigation; Robot sensing systems; Vectors; experience replay; learning sample; reinforcement learning; robot navigation;
Conference_Titel :
Computer Science and Automation Engineering (CSAE), 2012 IEEE International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-1-4673-0088-9
DOI :
10.1109/CSAE.2012.6273013
