Learning algorithms for finite horizon constrained Markov decision processes

Journal of Industrial and Management Optimization

Volumn 3, Issue 3, 2007, Pages 429-444

  Mittal, Anoop ^a   Hemachandra, N ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

Author keywords

Control of queues; Markov decision processes; Risk management; Supply chains

Indexed keywords

EID: 56649109020     PISSN: 15475816     EISSN: 1553166X     Source Type: Journal    
DOI: 10.3934/jimo.2007.3.429     Document Type: Article

References (20)

1. E. Altman, "Constrained Markov Decision Processes," Chapman & Hall, Boca Raton, 1999.
2. D. P. Bertsekas, "Dynamic Programming and Optimal Control," Athena Scientific, Belmont, 1995.
3. D. P. Bertsekas, and J. N. Tsitsiklis, "Neuro-Dynamic Programming," Athena Scientific, Belmont, 1996.
4. S. Bhatnagar, M. C. Fu, S. I. Marcus, and I-J Wang, Two-time scale simultaneous perturbation stochastic approximation using deterministic perturbation sequences, ACM Transactions on Modeling and Computer Simulation, 13, (2003), 180-209.
5. S. Bhatnagar and M. S. Abdulla, Simulation-Based Optimization Algorithms for Finite Horizon Markov Decision Processes, Submitted, 2006.
6. V. S. Borkar, An Actor-Critic Algorithm for Constrained Markov Decision Processes, Systems & Control Letters, 54 (2005), 207-213.
7. V. S. Borkar, Stochastic Approximation with Two Time Scales, Systems & Control Letters, 29 (1997), 291-294.
8. V. S. Borkar, Convex Analytic Methods in Markov Decision Processes Analysis, in "Handbook of Markov Decision Processes" (eds. E. A. Feinberg and A. Schwartz), Kluwer Academic Publishers, Dordrecht, 2001.
9. A. Chekhlov, S. Uryasev and M. Zabarankin, Drawdown Measure in Portfolio Optimization, Research Report 2003-15, ISE Dept. University of Florida, 2003.
10. C. Derman and M. Klein, Some Remarks on Finite Horizon Markovian Decision Models, Operations Research, 13 (1965), 272-278.
11. E. A. Feinberg and A. Schwartz (Editors), "Handbook of Markov Decision Processes," Kluwer Academic Publishers, Dordrecht, 2001.
12. Z. Gabor, Z. Kalmar and C. Szepesvari, Multi-Criteria Reinforcement Learning, Proceedings of the Fifteenth International Conference on Machine Learning, Madison, WI, (1998), 197-205.
13. F. Garcia and S. M. Nadiaye, A Learning Rate Analysis of Reinforcement Learning Algorithms in Finite-Horizon, Proceedings of the Fifteenth International Conference on Machine Learning, Madison, WI, (1998), 215-223.
14. E. D. Giorgi, A Note on Portfolio Selection under Various Risk Measures, IEW - Working Papers iewwp122, Institute for Empirical Research in Economics, IEW.
15. S. Mannor and N. Shimkin, A Geometric Approach to Multi-Criterion Reinforcement Learning, Journal of Machine Learning Research, 5 (2004), 325-360.
16. A. K. Mittal, "Learning Algorithms for Risk Management," M. Tech. Thesis, IEOR Interdisciplinary Programme, IIT Bombay, 2005.
17. M. L. Puterman, "Markov Decision Processes," Wiley, New York, 1994.
18. P. Sadhegh, Constrained Optimization via Stochastic Approximation with a Simultaneous Perturbation Gradient Approximation, Automatica, 33 (1997), 889-892.
19. J. C. Spall, A One-Measurement Form of Simultaneous Perturbation Stochastic Approximation, Automatica, 33 (1997), 109-112.
20. J. C. Spall, "Introduction to Stochastic Search and Optimization," Wiley, New York, 2003.