Robust dynamic programming

Mathematics of Operations Research

Volumn 30, Issue 2, 2005, Pages 257-280

  Iyengar, Garud N ^a  

^a Columbia University ^*  (United States)

Author keywords

Ambiguity; Dynamic programming; Markov decision processes; Robust optimization

Indexed keywords

AMBIGUITY; MARKOV DECISION PROCESSES; ROBUST OPTIMIZATION;

MARKOV PROCESSES; OPTIMIZATION; PUBLIC POLICY; ROBUSTNESS (CONTROL SYSTEMS); SENSITIVITY ANALYSIS;

DYNAMIC PROGRAMMING;

EID: 25444493818     PISSN: 0364765X     EISSN: 15265471     Source Type: Journal    
DOI: 10.1287/moor.1040.0129     Document Type: Review

References (25)

1. Altman, E., E. A. Feinberg, A. Shwartz. 2000. Weighted discounted games with perfect information. J. A. Filar, V. Gaitsgory, K. Mizukami, eds. Advances in Dynamic Games and Applications. Birkhauser, Boston, MA, 303-323.
2. Bagnell, J., A. Ng, J. Schneider. 2001. Solving uncertain Markov decision problems. Technical Report, Robotics Institute, CMU, CMU-RI-TR-01-25.
3. Ben-Tal, A., A. Nemirovski. 1997. Robust truss topology design via semidefinite programming. SIAM J. Optim. 7(4) 991-1016.
4. Ben-Tal, A., A. Nemirovski. 1998. Robust convex optimization. Math. Oper. Res. 23(4) 769-805.
5. Bertsekas, D. P., J. N. Tsitsiklis. 1996. Neuro-Dynamic Programming. Athena Scientific, Belmont, MA.
6. Cover, T. M. 1991. Universal portfolios. Math. Finance 1(1) 1-29.
7. Cover, T. M., J. A. Thomas. 1991. Elements of Information Theory. John Wiley and Sons, New York.
8. de Farias, D. P., B. Van Roy. 2003. The linear programming approach to approximate dynamic programming. Oper. Res. 51 850-865.
9. Ellsberg, D. 1961. Risk, ambiguity and the Savage axioms. Quart. J. Econom. 25(4) 643-669.
10. Epstein, L. G., M. Schneider. 2001. Recursive multiple priors. J. Econom. Theory 113(1) 1-31. http://rcer.econ.rochester.edu.
11. Epstein, L. G., M. Schneider. 2002. Learning under ambiguity. Technical Report 497, Rochester Center for Economic Research, http://rcer.econ.rochester.edu.
12. Gilboa, I., D. Schmeidler. 1989. Maxmin expected utility with non-unique priors. J. Math. Econom. 18 141-153.
13. Gillette, D. 1957. Stochastic games with zero stop probabilities. M. Dresher, A. W. Tucker, P. Wolfe, eds. Contributions to the Theory of Games, Vol. 3, Princeton University Press, Princeton, NJ, 179-187.
14. Goldfarb, D., G. Iyengar. 2003. Robust portfolio selection problems. Math. Oper. Res. 28(1) 1-38.
15. Hansen, L. P., T. J. Sargent. 2001. Robust control and model uncertainty. Amer. Econom. Rev. 91 60-66.
16. Littman, M. 1994. Memoryless policies: Theoretical limitations and practical results. D. Cliff, P. Husbands, S. W. Wilson, eds. Animals to Animals: SAB '94. MIT Press, Cambridge, MA, 238-245.
17. Nilim, A., L. El Ghaoui. 2002. Robust solutions to Markov decision problems with uncertain transition matrices. Oper. Res. Forthcoming.
18. Nilim, A., L. El Ghaoui. 2003. Robustness in Markov decision problems with uncertain transition matrices. Proc. NIPS.
19. Nowak, A. S. 1984. On zero-sum stochastic games with general state space. I. Probab. Math. Statist. 4 13-32.
20. Puterman, M. L. 1994. Markov Decision Processes: Discrete Stochastic Dynamic Programming. John Wiley and Sons
21. Satia, J. K. 1968. Markovian decision process with uncertain transition matrices or/and probabilistic observation of states. Ph.D. thesis, Stanford University, Stanford, CA.
22. Satia, J. K., R. L. Lave. 1973. Markov decision processes with uncertain transition probabilities. Oper. Res. 21(3) 728-740.
23. Shapiro, A., A. J. Kleywegt. 2002. Minimax analysis of stochastic problems. Optim. Methods and Software Forthcoming.
24. Simester, D. I., P. Sun, J. Tsitsiklis. 2005. Dynamic catalog mailing policies. Technical Report FRPS05-202, Fuqua School of Business. Duke University, Durham, NC.
25. White, C. C., H. K. Eldieb. 1994. Markov decision processes with imprecise transition probabilities. Oper. Res. 43 739-749.