Information-theoretic motor skill learning

AAAI Workshop - Technical Report

Volumn WS-13-10, Issue , 2013, Pages 59-65

  Neumann, Gerhard ^a   Daniel, Christian ^a   Kupcsik, Andras ^b   Deisenroth, Marc ^a   Peters, Jan ^a,c  

^a DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS;

CONTROL POLICY; CURRENT SITUATION; MOTOR SKILL LEARNING; MOTOR TASKS; POLICY SEARCH; REAL ROBOT; RELATIVE ENTROPY;

INFORMATION THEORY;

EID: 84898840923     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. Atkeson, C. G., and Santamaría, J. C. 1997. A Comparison of Direct and Model-Based Reinforcement Learning. In International Conference on Robotics and Automation (ICRA).
2. Bagnell, J. A., and Schneider, J. G. 2001. Autonomous Helicopter Control using Reinforcement Learning Policy Search Methods. In Proceedings of the International Conference for Robotics and Automation (ICRA), 1615-1620.
3. Ben Amor, H.; Berger, E.; Vogt, D.; and Jung, B. 2009. Kinesthetic bootstrapping: Teaching motor skills to humanoid robots through physical interaction. KI 2009: Advances in Artificial Intelligence 492-499.
4. da Silva, B. C.; Konidaris, G.; and Barto, A. G. 2012. Learning parameterized skills. In International Conference on Machine Learning.
5. Daniel, C.; Neumann, G.; and Peters, J. 2012a. Hierarchical Relative Entropy Policy Search. In International Conference on Artificial Intelligence and Statistics (AISTATS).
6. Daniel, C.; Neumann, G.; and Peters, J. 2012b. Learning Concurrent Motor Skills in Versatile Solution Spaces. In IEEE/RSJ International Conference on Intelligent Robots and Systems.
7. Daniel, C.; Neumann, G.; and Peters, J. 2013. Learning Sequential Motor Tasks. In IEEE International Conference on Robotics and Automation (ICRA).
8. Deisenroth, M. P., and Rasmussen, C. E. 2011. PILCO: A Model-Based and Data-Efficient Approach to Policy Search. In 28th International Conference on Machine Learning (ICML), 465-472.
9. Deisenroth, M. P.; Rasmussen, C. E.; and Fox, D. 2011. Learning to Control a Low-Cost Manipulator using Data-Efficient Reinforcement Learning. In Proceedings of R:SS.
10. Ijspeert, A. J., and Schaal, S. 2003. Learning Attractor Landscapes for Learning Motor Primitives. In Advances in Neural Information Processing Systems 15, (NIPS). Cambridge, MA: MIT Press.
11. Kober, J.; Mülling, K.; Kroemer, O.; Lampert, C. H.; Schölkopf, B.; and Peters, J. 2010. Movement Templates for Learning of Hitting and Batting. In International Conference on Robotics and Automation (ICRA).
12. Kober, J.; Oztop, E.; and Peters, J. 2010. Reinforcement Learning to adjust Robot Movements to New Situations. In Proceedings of the Robotics: Science and Systems Conference (RSS).
13. Kohl, N., and Stone, P. 2003. Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion. In International Conference for Robotics and Automation (ICRA).
14. Kormushev, P.; Calinon, S.; and Caldwell, D. G. 2010. Robot Motor Skill Coordination with EM-based Reinforcement Learning. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
15. Kupcsik, A.; Deisenroth, M. P.; Peters, J.; and Neumann, G. 2013. Data-Efficient Contextual Policy Search for Robot Movement Skills. In Proceedings of the National Conference on Artificial Intelligence (AAAI).
16. Neal, R., and Hinton, G. E. 1998. A View Of The Em Algorithm That Justifies Incremental, Sparse, And Other Variants. In Learning in Graphical Models, 355-368. Kluwer Academic Publishers.
17. Neumann, G. 2011. Variational Inference for Policy Search in Changing Situations. In Proceedings of the 28th International Conference on Machine Learning, (ICML 2011), 817-824. New York, NY, USA: ACM.
18. Peters, J., and Schaal, S. 2008. Reinforcement Learning of Motor Skills with Policy Gradients. Neural Networks (4):682-97.
19. Peters, J.; Mülling, K.; and Altun, Y. 2010. Relative Entropy Policy Search. In Proceedings of the 24th National Conference on Artificial Intelligence (AAAI). AAAI Press.
20. Rasmussen, C. E., and Williams, C. K. I. 2006. Gaussian Processes for Machine Learning. The MIT Press.
21. Schneider, J. G. 1997. Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning. In Advances in Neural Information Processing Systems (NIPS). 1047-1053.
22. Theodorou, E.; Buchli, J.; and Schaal, S. 2010. Reinforcement Learning of Motor Skills in High Dimensions: a Path Integral Approach. In Robotics and Automation (ICRA), 2010 IEEE International Conference on, 2397-2403.