M. N. Nicolescus and M. J. Mataric, “Natural Methods for Robot Task Learning: Instructive Demonstrations, Generalization and Practice,” In Proceedings of the Second International Joint Conference on Autonomous Agents and Multi-Agent Systems, Melbourne, Australia, July 14-18, 2003, pp. 241-248.

has been cited by the following article:

• TITLE: An Experience Based Learning Controller

  AUTHORS: Debadutt Goswami, Ping Jiang

  KEYWORDS: Mobile Robots, Learning from Demonstration, Neural Network Control, Reinforcement Learning

  JOURNAL NAME: Journal of Intelligent Learning Systems and Applications, Vol.2 No.2, June 1, 2010

  ABSTRACT: The autonomous mobile robots must be flexible to learn the new complex control behaviours in order to adapt effectively to a dynamic and varying environment. The proposed approach of this paper is to create a controller that learns the complex behaviours incorporating the learning from demonstration to reduce the search space and to improve the demonstrated task geometry by trial and corrections. The task faced by the robot has uncertainty that must be learned. Simulation results indicate that after the handful of trials, robot has learned the right policies and avoided the obstacles and reached the goal.