-
1
-
-
50549213583
-
Optimal control of Markov decision processes with incomplete state estimation
-
Aström, K. J. (1965). Optimal control of Markov decision processes with incomplete state estimation. Journal of Mathematical Analysis and Applications, 10, 403-406.
-
(1965)
Journal of Mathematical Analysis and Applications
, vol.10
, pp. 403-406
-
-
Aström, K.J.1
-
2
-
-
0029210635
-
Learning to act using real-time dynamic programming
-
Barto, A. G., Bradtke, S. J., & Singh, S. P. (1995). Learning to act using real-time dynamic programming. Artificial Intelligence, 72, 81-138.
-
(1995)
Artificial Intelligence
, vol.72
, pp. 81-138
-
-
Barto, A.G.1
Bradtke, S.J.2
Singh, S.P.3
-
6
-
-
0001811022
-
Structured reachability analysis for Markov decision processes
-
Boutilier, C., Brafman, R. I., & Geib, C. (1998). Structured reachability analysis for Markov decision processes. In Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI), pp. 24-32.
-
(1998)
Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI)
, pp. 24-32
-
-
Boutilier, C.1
Brafman, R.I.2
Geib, C.3
-
7
-
-
0030349220
-
Computing optimal policies for partially observable decision processes using compact representations
-
Portland, Oregon
-
Boutilier, C., & Poole, D. (1996). Computing optimal policies for partially observable decision processes using compact representations. In Thirteenth National Conference on Artificial Intelligence (AAAI), pp. 1168-1175. Portland, Oregon.
-
(1996)
Thirteenth National Conference on Artificial Intelligence (AAAI)
, pp. 1168-1175
-
-
Boutilier, C.1
Poole, D.2
-
8
-
-
0030570119
-
On the complexity of partially observed Markov decision processes
-
Burago, D., de Rougemont, M., & Slissekno, A. (1996). On the complexity of partially observed Markov decision processes. Theoretical Computer Science, 157(2), 161-183.
-
(1996)
Theoretical Computer Science
, vol.157
, Issue.2
, pp. 161-183
-
-
Burago, D.1
De Rougemont, M.2
Slissekno, A.3
-
11
-
-
0001909869
-
Incremental pruning: A simple, fast, exact method for partially observable Markov decision processes
-
Cassandra, A. R., Littman, M. L., & Zhang, N. L. (1997). Incremental pruning: a simple, fast, exact method for partially observable Markov decision processes. In Proceedings of the 13th Conference on Uncertainty in Artificial Intelligence, pp. 54-61.
-
(1997)
Proceedings of the 13th Conference on Uncertainty in Artificial Intelligence
, pp. 54-61
-
-
Cassandra, A.R.1
Littman, M.L.2
Zhang, N.L.3
-
12
-
-
27344447268
-
An environment model for nonstationary reinforcement learning
-
Choi, S. P. M., Yeung, D. Y., & Zhang, N. L. (1999). An environment model for nonstationary reinforcement learning. In Advances in Neural Information Processing Systems 12, pp. 987-993.
-
(1999)
Advances in Neural Information Processing Systems
, vol.12
, pp. 987-993
-
-
Choi, S.P.M.1
Yeung, D.Y.2
Zhang, N.L.3
-
13
-
-
85166375107
-
Solving planning problems with large state and action spaces
-
Pittsburgh, Pennsylvania
-
Dean, T., Givan, R., & Kim, K. (1998). Solving planning problems with large state and action spaces. In Proceedings of the 4th International Conference on Artificial Intelligence in Planning Systems (AIPS), pp. 102-110. Pittsburgh, Pennsylvania.
-
(1998)
Proceedings of the 4th International Conference on Artificial Intelligence in Planning Systems (AIPS)
, pp. 102-110
-
-
Dean, T.1
Givan, R.2
Kim, K.3
-
14
-
-
0027708037
-
Planning with deadlines in stochastic domains
-
Dean, T. L., Kaelbling, L. P., Kirman, J., & Nicholson, A. (1993). Planning with deadlines in stochastic domains. In Proceedings of the 9th National Conference on Artificial Intelligence (AAAI), pp. 574-579.
-
(1993)
Proceedings of the 9th National Conference on Artificial Intelligence (AAAI)
, pp. 574-579
-
-
Dean, T.L.1
Kaelbling, L.P.2
Kirman, J.3
Nicholson, A.4
-
21
-
-
0001770240
-
Value-function approximations for partially observable Markov decision processes
-
Hauskrecht, M. (2000). Value-function approximations for partially observable Markov decision processes. Journal of Artificial Intelligence Research, 13, 33-94.
-
(2000)
Journal of Artificial Intelligence Research
, vol.13
, pp. 33-94
-
-
Hauskrecht, M.1
-
23
-
-
0032073263
-
Planning and acting in partially observable stochastic domains
-
Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998). Planning and acting in partially observable stochastic domains. Artificial Intelligence, 101(1-2).
-
(1998)
Artificial Intelligence
, vol.101
, Issue.1-2
-
-
Kaelbling, L.P.1
Littman, M.L.2
Cassandra, A.R.3
-
25
-
-
0003596835
-
Efficient dynamic programming updates in partially observable Markov decision processes
-
Department of Computer Science, Brown University
-
Littman, M. L., Cassandra, A. R., & Kaelbling, L. P. (1995). Efficient dynamic programming updates in partially observable Markov decision processes. Tech. rep. CS-95-19, Department of Computer Science, Brown University.
-
(1995)
Tech. Rep.
, vol.CS-95-19
-
-
Littman, M.L.1
Cassandra, A.R.2
Kaelbling, L.P.3
-
26
-
-
11544375673
-
The computational complexity of probabilistic planning
-
Littman, M. L., Goldsmith, J., & Mundhenk, M. (1998). The computational complexity of probabilistic planning. Journal of Artificial Intelligence Research, 9, 1-36.
-
(1998)
Journal of Artificial Intelligence Research
, vol.9
, pp. 1-36
-
-
Littman, M.L.1
Goldsmith, J.2
Mundhenk, M.3
-
27
-
-
0000494894
-
Computationally feasible bounds for partially observed Markov decision processes
-
Lovejoy, W. S. (1991). Computationally feasible bounds for partially observed Markov decision processes. Operations Research, 39(1), 162-175.
-
(1991)
Operations Research
, vol.39
, Issue.1
, pp. 162-175
-
-
Lovejoy, W.S.1
-
29
-
-
0019909899
-
A survey of partially observable Markov decision processes: Theory, models, and algorithms
-
Monahan, G. E. (1982). A survey of partially observable Markov decision processes: theory, models, and algorithms. Management Science, 28(1), 1-16.
-
(1982)
Management Science
, vol.28
, Issue.1
, pp. 1-16
-
-
Monahan, G.E.1
-
30
-
-
0000977910
-
The complexity of Markov decision processes
-
Papadimitriou, C. H., & Tsitsiklis, J. N. (1987). The complexity of Markov decision processes. Mathematics of Operations Research, 12(3), 441-450.
-
(1987)
Mathematics of Operations Research
, vol.12
, Issue.3
, pp. 441-450
-
-
Papadimitriou, C.H.1
Tsitsiklis, J.N.2
-
33
-
-
84880772945
-
Point-based value iteration: An anytime algorithm for POMDPs
-
Pineau, J., Gordon, G., & Thrun, S. (2003). Point-based value iteration: an anytime algorithm for POMDPs. In International Joint Conference on Artificial Intelligence (IJCAI), pp. 1025-1032.
-
(2003)
International Joint Conference on Artificial Intelligence (IJCAI)
, pp. 1025-1032
-
-
Pineau, J.1
Gordon, G.2
Thrun, S.3
-
37
-
-
0015658957
-
The optimal control of partially observable Markov processes over a finite horizon
-
Smallwood, R. D., & Sondik, E. J. (1973). The optimal control of partially observable Markov processes over a finite horizon. Operations Research, 21, 1071-1088.
-
(1973)
Operations Research
, vol.21
, pp. 1071-1088
-
-
Smallwood, R.D.1
Sondik, E.J.2
-
38
-
-
0003871607
-
-
Ph.D. thesis, Stanford University, Stanford, California, USA
-
Sondik, E. J. (1971). The optimal control of partially observable decision processes. Ph.D. thesis, Stanford University, Stanford, California, USA.
-
(1971)
The Optimal Control of Partially Observable Decision Processes
-
-
Sondik, E.J.1
-
40
-
-
85016628903
-
A model approximation scheme for planning in partially observable stochastic domains
-
Zhang, N. L., & Liu, W. (1997). A model approximation scheme for planning in partially observable stochastic domains. Journal of Artificial Intelligence Research, 7, 199-230.
-
(1997)
Journal of Artificial Intelligence Research
, vol.7
, pp. 199-230
-
-
Zhang, N.L.1
Liu, W.2
-
42
-
-
0036374229
-
Speeding up the convergence of value iteration in partially observable Markov decision processes
-
Zhang, N. L., & Zhang, W. (2001b). Speeding up the convergence of value iteration in partially observable Markov decision processes. Journal of Artificial Intelligence Research, 14, 29-51.
-
(2001)
Journal of Artificial Intelligence Research
, vol.14
, pp. 29-51
-
-
Zhang, N.L.1
Zhang, W.2
-
43
-
-
0003881464
-
-
Ph.D. thesis, Department of Computer Science, the Hong Kong University of Science and Technology
-
Zhang, W. (2001). Algorithms for partially observable Markov decision processes. Ph.D. thesis, Department of Computer Science, the Hong Kong University of Science and Technology.
-
(2001)
Algorithms for Partially Observable Markov Decision Processes
-
-
Zhang, W.1
-
46
-
-
84867833986
-
A POMDP approximation algorithm that anticipates the need to observe
-
Lecture Notes in Computer Science, New York: Springer-Verlag
-
Zubek, V. B., & Dietterich, T. G. (2000). A POMDP approximation algorithm that anticipates the need to observe. In Proceedings of PRICAI-2000, pp. 521-532. Lecture Notes in Computer Science, New York: Springer-Verlag.
-
(2000)
Proceedings of PRICAI-2000
, pp. 521-532
-
-
Zubek, V.B.1
Dietterich, T.G.2
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