Interactive control of diverse complex characters with neural networks

Advances in Neural Information Processing Systems

Volumn 2015-January, Issue , 2015, Pages 3132-3140

  Mordatch, Igor ^a   Lowrey, Kendall ^a   Andrew, Galen ^a   Popovic, Zoran ^a   Todorov, Emanuel ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX NETWORKS; CONTROLLERS; DYNAMICAL SYSTEMS; INFORMATION SCIENCE;

COMPLEX CHARACTER; ESSENTIAL FEATURES; INTERACTIVE CONTROL; OPTIMAL FEEDBACK GAINS; PHYSICAL SYSTEMS; QUADRUPED WALKING; TASK SPECIFICATIONS; TRAJECTORY OPTIMIZATION;

RECURRENT NEURAL NETWORKS;

EID: 84965182099     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. P. Chen. Hessian matrix vs. gauss-newton hessian matrix. SIAM J. Numerical Analysis, 49(4):1417-1435, 2011.
2. H. Geyer and H. Herr. A muscle-reflex model that encodes principles of legged mechanics produces human walking dynamics and muscle activities. Neural Systems and Rehabilitation Engineering, IEEE Transactions on, 18(3):263-273, 2010.
3. R. Grzeszczuk, D. Terzopoulos, and G. Hinton. Neuroanimator: Fast neural network emulation and control of physics-based models. In Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH'98, pages 9-20, New York, NY, USA, 1998. ACM.
4. G. E. Hinton, N. Srivastava, A. Krizhevsky, I. Sutskever, and R. R. Salakhutdinov. Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580, 2012.
5. G. M. Hoerzer, R. Legenstein, and W. Maass. Emergence of complex computational structures from chaotic neural networks through reward-modulated hebbian learning. Cerebral Cortex, 2012.
6. D. Huh and E. Todorov. Real-time motor control using recurrent neural networks. In Adaptive Dynamic Programming and Reinforcement Learning, 2009. ADPRL'09. IEEE Symposium on, pages 42-49, March 2009.
7. A. J. Ijspeert. Central pattern generators for locomotion control in animals and robots: a review, 2008.
8. E. Ju, J. Won, J. Lee, B. Choi, J. Noh, and M. G. Choi. Data-driven control of flapping flight. ACM Trans. Graph., 32(5):151:1-151:12, Oct. 2013.
9. S. Levine and V. Koltun. Learning complex neural network policies with trajectory optimization. In ICML'14: Proceedings of the 31st International Conference on Machine Learning, 2014.
10. V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. A. Riedmiller. Playing atari with deep reinforcement learning. CoRR, abs/1312.5602, 2013.
11. I. Mordatch and E. Todorov. Combining the benefits of function approximation and trajectory optimization. In Robotics: Science and Systems (RSS), 2014.
12. I. Mordatch, E. Todorov, and Z. Popović. Discovery of complex behaviors through contactinvariant optimization. ACM Transactions on Graphics (TOG), 31(4):43, 2012.
13. J. R. Rebula, P. D. Neuhaus, B. V. Bonnlander, M. J. Johnson, and J. E. Pratt. A controller for the littledog quadruped walking on rough terrain. In Robotics and Automation, 2007 IEEE International Conference on, pages 1467-1473. IEEE, 2007.
14. J. Schulman, S. Levine, P. Moritz, M. I. Jordan, and P. Abbeel. Trust region policy optimization. CoRR, abs/1502.05477, 2015.
15. I. Sutskever, J. Martens, G. E. Dahl, and G. E. Hinton. On the importance of initialization and momentum in deep learning. In Proceedings of the 30th International Conference on Machine Learning (ICML-13), volume 28, pages 1139-1147, May 2013.
16. E. Todorov, T. Erez, and Y. Tassa. Mujoco: A physics engine for model-based control. In IROS'12, pages 5026-5033, 2012.
17. P. Vincent, H. Larochelle, Y. Bengio, and P.-A. Manzagol. Extracting and composing robust features with denoising autoencoders. pages 1096-1103, 2008.
18. M. Vukobratovic and B. Borovac. Zero-moment point-thirty five years of its life. I. J. Humanoid Robotics, 1(1):157-173, 2004.
19. S. Wager, S. Wang, and P. Liang. Dropout training as adaptive regularization. In Advances in Neural Information Processing Systems (NIPS), 2013.
20. J. M. Wang, D. J. Fleet, and A. Hertzmann. Optimizing walking controllers for uncertain inputs and environments. ACM Trans. Graph., 29(4):73:1-73:8, July 2010.
21. K. Yin, K. Loken, and M. van de Panne. Simbicon: Simple biped locomotion control. ACM Trans. Graph., 26(3): Article 105, 2007.