-
2
-
-
84880685295
-
Prioritized goal decomposition of Markov decision processes: Toward a synthesis of classical and decision theoretic planning
-
Nagoya
-
C. Boutilier, R. I. Brafman, and C. Geib. Prioritized goal decomposition of Markov decision processes: Toward a synthesis of classical and decision theoretic planning. In Proc. Fifteenth International Joint Conf. on AI, pp.1156-1162, Nagoya, 1997.
-
(1997)
Proc. Fifteenth International Joint Conf. on AI
, pp. 1156-1162
-
-
Boutilier, C.1
Brafman, R.I.2
Geib, C.3
-
4
-
-
0002192119
-
Input generalization in delayed reinforcement learning: An algorithm and performance comparisons
-
Sydney
-
D. Chapman and L. P. Kaelbling. Input generalization in delayed reinforcement learning: An algorithm and performance comparisons. In Proc. Twelfth International Joint Conf. on AI, pp.726-731, Sydney, 1991.
-
(1991)
Proc. Twelfth International Joint Conf. on AI
, pp. 726-731
-
-
Chapman, D.1
Kaelbling, L.P.2
-
5
-
-
0000746330
-
Model reduction techniques for computing approximately optimal solutions for Markov decision processes
-
Providence, RI
-
T. Dean, R. Givan, and S. Leach. Model reduction techniques for computing approximately optimal solutions for Markov decision processes. In Proc. Thirteenth Conf. on Uncertainty in AI, pp.124-131, Providence, RI, 1997.
-
(1997)
Proc. Thirteenth Conf. on Uncertainty in AI
, pp. 124-131
-
-
Dean, T.1
Givan, R.2
Leach, S.3
-
6
-
-
84990553353
-
A model for reasoning about persistence and causation
-
T. Dean and K. Kanazawa. A model for reasoning about persistence and causation. Comput. Intel, 5(3): 142-150, 1989.
-
(1989)
Comput. Intel
, vol.5
, Issue.3
, pp. 142-150
-
-
Dean, T.1
Kanazawa, K.2
-
7
-
-
0030697013
-
Abstraction and approximate decision theoretic planning
-
R. Dearden and C. Boutilier. Abstraction and approximate decision theoretic planning. Artif. Intel, 89:219-283, 1997.
-
(1997)
Artif. Intel
, vol.89
, pp. 219-283
-
-
Dearden, R.1
Boutilier, C.2
-
10
-
-
0002956570
-
SPUDD: Stochastic planning using decision diagrams
-
Stockholm
-
J. Hoey, R. St-Aubin, A. Hu, and C. Boutilier. SPUDD: Stochastic planning using decision diagrams. In Proc. Fifteenth Conf. on Uncertainty in AI, pp.279-288, Stockholm, 1999.
-
(1999)
Proc. Fifteenth Conf. on Uncertainty in AI
, pp. 279-288
-
-
Hoey, J.1
St-Aubin, R.2
Hu, A.3
Boutilier, C.4
-
12
-
-
0031632806
-
Solving very large weakly coupled Markov decision processes
-
Madison, WI
-
N. Meuleau, M. Hauskrecht, K. Kim, L. Peshkin, L. P. Kaelbling, T. Dean, and C. Boutilier. Solving very large weakly coupled Markov decision processes. In Proc. Fifteenth National Conf. on AI, pp.165-172, Madison, WI, 1998.
-
(1998)
Proc. Fifteenth National Conf. on AI
, pp. 165-172
-
-
Meuleau, N.1
Hauskrecht, M.2
Kim, K.3
Peshkin, L.4
Kaelbling, L.P.5
Dean, T.6
Boutilier, C.7
-
13
-
-
0029514510
-
The parti-game algorithm for variable resolution reinforcement learning in multidimensional state spaces
-
A. W. Moore and C. G. Atkeson. The parti-game algorithm for variable resolution reinforcement learning in multidimensional state spaces. Mach. Learn., 21:199-234, 1995.
-
(1995)
Mach. Learn.
, vol.21
, pp. 199-234
-
-
Moore, A.W.1
Atkeson, C.G.2
-
17
-
-
84899022377
-
How to dynamically merge Markov decision processes
-
MIT Press, Cambridge
-
S. P. Singh and D. Cohn. How to dynamically merge Markov decision processes. In Advances in Neural Info. Processing Sys. 10, pp.1057-1063. MIT Press, Cambridge, 1998.
-
(1998)
Advances in Neural Info. Processing Sys.
, vol.10
, pp. 1057-1063
-
-
Singh, S.P.1
Cohn, D.2
-
18
-
-
0029752470
-
Feature-based methods for large scale dynamic programming
-
J. Tsitsiklis and B. Van Roy. Feature-based methods for large scale dynamic programming. Mach. Learn., 22:59-94, 1996.
-
(1996)
Mach. Learn.
, vol.22
, pp. 59-94
-
-
Tsitsiklis, J.1
Van Roy, B.2
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