Autonomous Vehicle Navigation Behavior Generation by Reinforcement Learning
Keitaro Naruse* and Yukinori Kakazu* and Ming C. Leu**
*Hokkaido University, Kita-13 Nishi-8, Sapporo 060 Japan
**New Jersey Institute of Technology, Newark, NJ 07102, USA
Received:April 3, 1998Accepted:August 17, 1998Published:October 20, 1998
Keywords:Reinforcement learning, Behavior robotics, Autonomous vehicle navigation, Path planning, Nonholononic vehicle
This paper presents an efficient reinforcement learning algorithm for autonomous vehicle navigation. Efficiency is achieved by identifying the structure of a given problem, and it is represented as a set of behaviors - efficient action sequences for solving the problem. Computational simulations are conducted and the proposed mechanism demonstrate.
Cite this article as:K. Naruse, Y. Kakazu, and M. Leu, “Autonomous Vehicle Navigation Behavior Generation by Reinforcement Learning,” J. Robot. Mechatron., Vol.10 No.5, pp. 413-417, 1998.Data files: