A unifying framework for linearly solvable control

Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence, UAI 2011

Volumn , Issue , 2011, Pages 179-186

  Dvijotham, Krishnamurthy ^a   Todorov, Emanuel ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONTINUOUS TIME SYSTEMS; MARKOV PROCESSES; QUANTUM THEORY; STOCHASTIC SYSTEMS;

COMPOSITIONALITY; CONTINUOUS PARAMETERS; CONTINUOUS TIME LIMITS; CONTROL PROBLEMS; MARKOV DECISION PROCESSES; SOLVABLE CONTROLS; STOCHASTIC POLICY; VALUE FUNCTIONS;

DECISION THEORY;

EID: 80053143654     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (14)

1. Başar, T., & Bernhard, P. 1995. H-infinity optimal control and related minimax design problems: a dynamic game approach. Birkhauser.
2. Broek, B. Van Den, Wiegerinck, W., & Kappen, B. 2010. Risk sensitive path integral control. In: Uncertainty in ai, 2010. proceedings of the 2010.
3. Da Silva, M., Durand, F., & Popović, J. 2009. Linear Bellman combination for control of character animation. Acm transactions on graphics (tog), 28(3), 1-10.
4. Fleming, W., & McEneaney, W. 1992. Risk sensitive optimal control and differential games. Stochastic theory and adaptive control, 185-197.
5. Jacobson, D.H. 1973. Optimal stochastic linear systems with exponential performance criteria and their relation to deterministic differential games. Ieee transactions on automatic control, 18, 124-131.
6. Jaśkiewicz, A. 2007. Average optimality for risk-sensitive control with general state space. The annals of applied probability, 17(2), 654-675.
7. Kappen, H.J. 2005. Linear theory for control of non-linear stochastic systems. Physical review letters, 95(20), 200201.
8. Marcus, S.I., Fernández-Gaucherand, E., Hernández- Hernandez, D., Coraluppi, S., & Fard, P. 1997. Risk sensitive Markov decision processes. Systems and control in the twenty-first century, 29.
9. Mensink, T., Verbeek, J., & Kappen, H.J. 2010. Ep for efficient stochastic control with obstacles. Ecai, 1-6. Accepted.
10. Øksendal, B.K. 2003. Stochastic differential equations: an introduction with applications. Springer Verlag.
11. Serre, D. 2010. Matrices: Theory and applications. Springer Verlag.
12. Theodorou, E., Buchli, J., & Schaal, S. 2010. Rein-forcement learning of motor skills in high dimen-sions: A path integral approach. Pages 2397-2403 of: Robotics and automation (icra), 2010 ieee international conference on. IEEE.
13. Todorov, E. 2009. Efficient computation of optimal actions. Proceedings of the national academy of sciences, 106(28), 11478.
14. Van Erven, T., & Harremoes, P. 2010. Renyi divergence and majorization. Pages 1335-1339 of: Information theory proceedings (isit), 2010 ieee international symposium on.