Partially observable markov decision processes for artificial intelligence

• Astrom, K. J. (1965), Optimal control of Markov decision processes with incomplete state estimation, Journal of Mathematical Analysis and Applications 10, 174–205

  Article  Google Scholar 

• Boutilier, C. & Dearden, R. (1994), Using abstractions for decision theoretic planning with time constraints, in Proceedings of the Twelfth National Conference on Artificial Intelligence

  Google Scholar 

• Boutilier, C., Dearden, R. & Goldszmidt, M. (1995), Exploiting structure in policy construction, in Proceedings of the International Joint Conference on Artificial Intelligence

  Google Scholar 

• Cassandra, A. R. (1994), Algorithms for partially observable Markov decision processes, Technical Report CS-94-14, Brown University, Providence, Rhode Island

  Google Scholar 

• Cheng, H.-T. (1988), Algorithms for Partially Observable Markov Decision Processes, PhD thesis, University of British Columbia, British Columbia, Canada

  Google Scholar 

• Dean, T., Kaelbling, L. P., Kirman, J. & Nicholson, A. (To Appear), Planning under time constraints in stochastic domains, Artificial Intelligence

  Google Scholar 

• Drummond, M. & Bresina, J. (1990), Anytime synthetic projection, in Proceedings of the Eighth National Conference on Artificial Intelligence, Morgan Kaufmann, pp. 138–144

  Google Scholar 

• Howard, R. A. (1960), Dynamic Programming and Markov Processes, The MIT Press, Cambridge, Massachusetts

  Google Scholar 

• Kalman, R. E. (1960), A new approach to linear filtering and prediction problems, Transactions of the American Society of Mechanical Engineers Journal of Basic Engineering 82, 35–45

  Google Scholar 

• Kushmerick, N., Hanks, S. & Weld, D. (1993), An Algorithm for Probabilistic Planning, Technical Report 93-06-03, University of Washington Department of Computer Science and Engineering. To appear in Artificial Intelligence.

  Google Scholar 

• Littman, M. L. (1994), The witness algorithm: Solving partially observable Markov decision processes, Technical Report CS-94-40, Brown University, Providence, Rhode Island

  Google Scholar 

• Littman, M. L., Cassandra, A. R. & Kaelbling, L. P. (1995 a), An efficient algorithm for dynamic programming in partially observable Markov decision processes, Technical Report CS-95-19, Brown University, Providence, Rhode Island

  Google Scholar 

• Littman, M. L., Cassandra, A. R. & Kaelbling, L. P. (1995 b), Learning policies for partially observable environments: Scaling up, in Proceedings of the Twelfth International Conference on Machine Learning, Morgan Kaufmann

  Google Scholar 

• Lovejoy, W. S. (1991), A survey of algorithmic methods for partially observed Markov decision processes, Annals of Operations Research 28(1), 47–65

  Article  Google Scholar 

• Monahan, G. E. (1982), A survey of partially observable Markov decision processes: Theory, models, and algorithms, Management Science 28(1), 1–16

  Google Scholar 

• Moore, R. C. (1985), A formal theory of knowledge and action, in J. R. Hobbs & R. C. Moore (eds.) Formal Theories of the Commonsense World, Ablex Publishing Company, Norwood, New Jersey

  Google Scholar 

• Puterman, M. L. (1994), Markov Decision Processes, John Wiley & Sons, New York

  Google Scholar 

• Singh, S. P., Jaakkola, T. & Jordan, M.I. (1994), Model-free reinforcement learning for non-Markovian decision problems, in Machine Learning: Proceedings of the Eleventh International Conference, Morgan Kaufmann, San Francisco, California, pp. 284–292

  Google Scholar 

• Smallwood, R. D. & Sondik, E. J. (1973), The optimal control of partially observable Markov processes over a finite horizon, Operations Research 21, 1071–1088

  Google Scholar 

• Sondik, E. J. (1978), The optimal control of partially observable Markov processes over the infinite horizon: Discounted costs, Operations Research 26(2), 282–304

  Google Scholar 

• Tseng, P. (1990), Solving H-horizon, stationary Markov decision problems in time proportional to log (H), Operations Research Letters 9(5), 287–297

  Article  Google Scholar 

• White, III, C. C. (1991), Partially observed Markov decision processes: A survey, Annals of Operations Research

  Google Scholar 

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