Learning to Select Primitives and Generate Sub-goals from Practice

IEEE International Conference on Intelligent Robots and Systems

Volumn 1, Issue , 2003, Pages 946-953

  Bentivegna, Darrin C ^a,b   Atkeson, Christopher G ^a,c   Cheng, Gordon ^a  

^a ADVANCED TELECOMMUNICATIONS RESEARCH INSTITUTE INTERNATIONAL   (Japan)

^b Georgia Institute of Technology   (United States)

^c CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVORIAL PRIMITIVES; RANDOM ACTIONS;

ALGORITHMS; BEHAVIORAL RESEARCH; COMPUTER HARDWARE; COMPUTER SOFTWARE; GAME THEORY; INFORMATION RETRIEVAL; INVERSE KINEMATICS; LEARNING SYSTEMS;

ROBOTICS;

EID: 0348040468     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. R. C. Arkin. Behavior-Based Robotics. MIT Press, Cambridge, MA, 1998.
2. C. G. Atkeson, A. W. Moore, and S. Schaal. Locally weighted learning. Artificial Intelligence Review, 11:11-73, 1997.
3. D. C. Bentivegna and C. G. Atkeson. Learning from observation using primitives. In Proceedings of the IEEE International Conference on Robotics and Automation, Seoul, Korea, 2001.
4. D. C. Bentivegna and C. G. Atkeson. A framework for learning from observation using primitives. In Proceedings of the RoboCup 2002 International Symposium., Fukuoka, Japan, 2002.
5. D. C. Bentivegna, A. Ude, C. G. Atkeson, and G. Cheng. Humanoid robot learning and game playing using pc-based vision. In Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems., Switzerland, 2002.
6. A. Fod, M. Mataric, and O. Jenkins. Automated derivation of primitives for movement classification. In First IEEE-RAS International Conference on Humanoid Robotics (Humanoids-2000), MIT, Cambridge, MA, 2000.
7. Y. Kuniyoshi, M. Inaba, and H. Inoue. Learning by watching: Extracting reusable task knowledge from visual observation of human performance. In IEEE Transactions on Robotics and Automation, pages 799-822, 1994.
8. M. J. Mataric, M. Williamson, J. Demiris, and A. Mohan. Behavior-based primitives for articulated control. In Fifth International Conference on Simulation of Adaptive Behavior (SAB-98), pages 165-170. MIT Press, 1998.
9. A. McGovern and A. G. Barto. Automatic discovery of subgoals in reinforcement learning using diverse density. In Proceedings of the 18th International Conference on Machine Learning, 2001.
10. S. Schaal, C. Atkeson, and S. Vijayakumar. Scalable locally weighted statistical techniques for real time robot learning. In Applied Intelligence - Special issue on Scalable Robotic Applications of Neural Networks, volume 17, pages 49-60, 2002.
11. R. A. Schmidt. Motor Learning and Control. Human Kinetics Publishers, Champaign, IL, 1988.
12. R. Sutton and A. Barto. Reinforcment Learning: An Introduction. MIT Press, 1998.
13. C. Tung and A. Kak. Automatic learning of assembly tasks using a dataglove system. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, volume 1, 1995.
14. S. Vijayakumar, A. DŚouza, T. Shibata, J. Conradt, and S. Schaal. Statistical learning for humanoid robots. In Autonomous Robot, volume 12, pages 55-69, 2002.
15. S. Vijayakumar and S. Schaal. Locally weighted projection regression: An O(n) algorithm for incremental real time learning in high dimensional spaces. In Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford, CA, 2000.