Q-learning Based on Neural Network in Learning Action Selection of Mobile Robot

摘要：

This paper focuses on the learning action selection in behavior-based autonomous mobile robot.Autonomous mobile robot needs a large space to store the state-action pair in the application of tabular Q-learning.Neural network has a good ability of generalization,so in this paper Q-learning based on neural network is developed which has a good ability to approximate to Q-function.The Q-learning based on neural network is applied to autonomous mobile robot for goal directed obstacle avoidance.Results of simulation show that the mobile robot can learn to select proper actions itself to accomplish the task autonomously.

关键词： Behavior-based mobile robot Reinforcement learning Neural Network Q-learning Obstacle Avoidance

作者: Junfei Qiao Zhanjun Hou Xiaogang Ruan

作者单位: Institute of Artificial Intelligence and Robotics,School of Electronic Information and Control Engineering Beijing University of Technology Pingleyuan 100＃,Chaoyang District,Beijing,China

会议类型: 国际会议

会议名称: 2007 IEEE International Conference on Automation and Lofistics

会议地点: 山东济南

会议语种:英文

在线出版日期: 2007-08-18（万方平台首次上网日期，不代表论文的发表时间）