Teaching robots to coordinate its behaviours

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 2004, Issue 4, 2004, Pages 3721-3726

  Gu, Dongbing ^a   Hu, Huosheng ^a  

^a UNIVERSITY OF ESSEX   (United Kingdom)

Author keywords

Behaviour co ordination; Reinforcement learning; Robot learning

Indexed keywords

BEHAVIORAL RESEARCH; COLOR; DATA ACQUISITION; LEARNING ALGORITHMS; LEARNING SYSTEMS; NEURAL NETWORKS; ROBOTICS; VECTORS;

BEHAVIOUR CO-ORDINATION; REINFORCEMENT LEARNING; TEACHING ROBOTS;

ROBOT LEARNING;

EID: 3042644317     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/robot.2004.1308842     Document Type: Conference Paper

References (14)

1. Arkin, R. C., Behaviour-based Robotics, The MIT Press, 1998.
2. Breazeal, C. and Scassellati, B., Robots that imitate humans, Trends in Cognitive Science, vol. 6, 2002, pages 481-487.
3. Brooks, R., A Robust Layered Control System for a Mobile Robot, IEEE J. Robotics and Automation, Vol. 2, No.l, 1986, pages 14-23.
4. Dorigo, M. and Colombetti, M., The Role of the Trainer in Reinforcement Learning, Proceedings of MLC-COLT 94 Workshop on Robot Learning, July 10th, New Brunswick, NJ, 1994.
5. Huber, M., A hybrid Architecture for Hierarchical Reinforcement Learning, Proceeding of 2000 IEEE Int. Conf. on Robotics & Automation, Detroit San Francisco, April 2000, pages 3290-3295.
6. Kaelbling, L. P. and Moor, A. W., Reinforcement Learning: A Survey, Journal of Artificial Intelligence Research, 4 (1996), pages 237-285.
7. Lin, Long-Ji, Self-improving Reactive Agents Based on Reinforcement learning, planning, and teaching, Machine Learning, Vol. 55, 1992, pages 293-321.
8. Martinson, E., Stoytchev, A., and Arkin, R., Robot Behavioural Selection Using Q-learning, Proceedings of 2002 Int. Conf. on Robotics and Automation, Washinton D.C., May 2002.
9. Mataric, M. j., Reinforcement Learning in the Multi-Robot Domain, Autonomous Robots, 4(1), March 1997, pages 73-83.
10. Pirjanian, P., Behaviour Co-ordination Mechanism - State-of-the -art, Tech-report IRIS-99-375, Institute for Robotics and Intelligent Systems, School of Engineering, University of Southern California, October, 1999.
11. Pomerleau, D., Neural Networks for Intelligent Vehicles, Proceedings of the 1993 Intelligent Vehicles Conference, July 1993, pages 19-24.
12. Schaal, S., Is Imitation Learning the Route to Humanoid Robots? Trends in Cognitive Sciences, vol. 3, 1999, pages 233-242.
13. Smart, W. D. and Kaelbling, L. P., Effective Reinforcement Learning for Mobile Robots, Proceedings of the IEEE International Conference on Robotics and Automation, 2002.
14. Sutton, R. S. and Barto, A.G., Introduction to Reinforcement Learning, MIT Press, 1998.