-
1
-
-
0033897011
-
Using temporal logics to express search control knowledge for planning
-
Bacchus, F., & Kabanza, F. (2000). Using temporal logics to express search control knowledge for planning. Artificial Intelligence, 116, 123-191.
-
(2000)
Artificial Intelligence
, vol.116
, pp. 123-191
-
-
Bacchus, F.1
Kabanza, F.2
-
4
-
-
0032069371
-
Top-down induction of first-order logical decision trees
-
Blockeel, H., & De Raedt, L. (1998). Top-down induction of first-order logical decision trees. Artificial Intelligence, 101, 285-297.
-
(1998)
Artificial Intelligence
, vol.101
, pp. 285-297
-
-
Blockeel, H.1
De Raedt, L.2
-
6
-
-
84880891360
-
Symbolic dynamic programming for first-order MDPs
-
Boutilier, C., Reiter, R., & Price, B. (2001). Symbolic dynamic programming for first-order MDPs. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, pp. 690-700.
-
(2001)
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence
, pp. 690-700
-
-
Boutilier, C.1
Reiter, R.2
Price, B.3
-
9
-
-
4444312102
-
Integrating guidance into relational reinforcement learning
-
Driessens, K., & Džeroski, S. (2004). Integrating guidance into relational reinforcement learning. Machine Learning, 57, 271-304.
-
(2004)
Machine Learning
, vol.57
, pp. 271-304
-
-
Driessens, K.1
Džeroski, S.2
-
10
-
-
33748273074
-
Graph kernels and gaussian processes for relational reinforcement learning
-
Driessens, K., Ramon, J., & Gärtner, T. (2006). Graph kernels and gaussian processes for relational reinforcement learning. Machine Learning, 64, 91-119.
-
(2006)
Machine Learning
, vol.64
, pp. 91-119
-
-
Driessens, K.1
Ramon, J.2
Gärtner, T.3
-
11
-
-
0035312760
-
Relational reinforcement learning
-
DOI 10.1023/A:1007694015589
-
Džeroski, S., DeRaedt, L., & Driessens, K. (2001). Relational reinforcement learning. Machine Learning, 43, 7-52. (Pubitemid 32286614)
-
(2001)
Machine Learning
, vol.43
, Issue.1-2
, pp. 7-52
-
-
Dzeroski, S.1
De Raedt, L.2
Driessens, K.3
-
12
-
-
84948981620
-
Handling real numbers in ILP: A step towards better behavioural clones
-
Dzeroski, S., Todorovski, L., & Urbancic, T. (1995). Handling real numbers in ILP: A step towards better behavioural clones. In Proceedings of the Eighth European Conference on Machine Learning, pp. 283-286.
-
(1995)
Proceedings of the Eighth European Conference on Machine Learning
, pp. 283-286
-
-
Dzeroski, S.1
Todorovski, L.2
Urbancic, T.3
-
16
-
-
0030087080
-
Knowledge-based feature discovery for evaluation functions
-
Fawcett, T. (1996). Knowledge-based feature discovery for evaluation functions. Computational Intelligence, 12(1), 42-64.
-
(1996)
Computational Intelligence
, vol.12
, Issue.1
, pp. 42-64
-
-
Fawcett, T.1
-
17
-
-
13444258086
-
Learning domain-specific control knowledge from random walks
-
Fern, A., Yoon, S., & Givan, R. (2004). Learning domain-specific control knowledge from random walks. In Proceedings of the Fourteenth International Conference on Automated Planning and Scheduling, pp. 191-199.
-
(2004)
Proceedings of the Fourteenth International Conference on Automated Planning and Scheduling
, pp. 191-199
-
-
Fern, A.1
Yoon, S.2
Givan, R.3
-
18
-
-
33744466799
-
Approximate policy iteration with a policy language bias: Solving relational Markov decision processes
-
Fern, A., Yoon, S., & Givan, R. (2006). Approximate policy iteration with a policy language bias: Solving relational Markov decision processes. Journal of Artificial Intelligence Research, 25, 75-118.
-
(2006)
Journal of Artificial Intelligence Research
, vol.25
, pp. 75-118
-
-
Fern, A.1
Yoon, S.2
Givan, R.3
-
23
-
-
84880898477
-
Max-norm projections for factored MDPs
-
Guestrin, C., Koller, D., & Parr, R. (2001). Max-norm projections for factored MDPs. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence, pp. 673-680.
-
(2001)
Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence
, pp. 673-680
-
-
Guestrin, C.1
Koller, D.2
Parr, R.3
-
24
-
-
38049183848
-
FluCaP: A heuristic search planner for first-order MDPs
-
Holldobler, S., Karabaev, E., & Skvortsova, O. (2006). FluCaP: A heuristic search planner for first-order MDPs. Journal of Artificial Intelligence Research, 27, 419-439.
-
(2006)
Journal of Artificial Intelligence Research
, vol.27
, pp. 419-439
-
-
Holldobler, S.1
Karabaev, E.2
Skvortsova, O.3
-
27
-
-
0030416991
-
Failure driven dynamic search control for partial order planners: An explanation based approach
-
Kambhampati, S., Katukam, S., & Qu, Y. (1996). Failure driven dynamic search control for partial order planners: An explanation based approach. Artificial Intelligence, 88(1-2), 253-315.
-
(1996)
Artificial Intelligence
, vol.88
, Issue.1-2
, pp. 253-315
-
-
Kambhampati, S.1
Katukam, S.2
Qu, Y.3
-
29
-
-
33749263205
-
Automatic basis function construction for approximate dynamic programming and reinforcement learning
-
Keller, P., Mannor, S., & Precup, D. (2006). Automatic basis function construction for approximate dynamic programming and reinforcement learning. In Proceedings of the Twenty-Third International Conference on Machine Learning, pp. 449-456.
-
(2006)
Proceedings of the Twenty-Third International Conference on Machine Learning
, pp. 449-456
-
-
Keller, P.1
Mannor, S.2
Precup, D.3
-
30
-
-
14344249892
-
Bellman goes relational
-
Kersting, K., Van Otterlo, M., & De Raedt, L. (2004). Bellman goes relational. In Proceedings of the Twenty-First International Conference on Machine Learning, pp. 465-472.
-
(2004)
Proceedings of the Twenty-First International Conference on Machine Learning
, pp. 465-472
-
-
Kersting, K.1
Van Otterlo, M.2
De Raedt, L.3
-
32
-
-
0033189384
-
Learning action strategies for planning domains
-
Khardon, R. (1999). Learning action strategies for planning domains. Artificial Intelligence, 113(1-2), 125-148.
-
(1999)
Artificial Intelligence
, vol.113
, Issue.1-2
, pp. 125-148
-
-
Khardon, R.1
-
33
-
-
35048819671
-
Least-squares methods in reinforcement learning for control
-
Lagoudakis, M. G., Parr, R., & Littman, M. L. (2002). Least-squares methods in reinforcement learning for control. In SETN 02: Proceedings of the Second Hellenic Conference on AI, pp. 249-260.
-
(2002)
SETN 02: Proceedings of the Second Hellenic Conference on AI
, pp. 249-260
-
-
Lagoudakis, M.G.1
Parr, R.2
Littman, M.L.3
-
34
-
-
35748957806
-
Proto-value functions: A Laplacian framework for learning representation and control in Markov decision processes
-
Mahadevan, S., & Maggioni, M. (2007). Proto-value functions: A Laplacian framework for learning representation and control in Markov decision processes. Journal of Machine Learning Research, 8, 2169-2231.
-
(2007)
Journal of Machine Learning Research
, vol.8
, pp. 2169-2231
-
-
Mahadevan, S.1
Maggioni, M.2
-
35
-
-
1142281116
-
Learning generalized policies from planning examples using concept languages
-
Martin, M., & Geffner, H. (2004). Learning generalized policies from planning examples using concept languages. Applied Intelligence, 20, 9-19.
-
(2004)
Applied Intelligence
, vol.20
, pp. 9-19
-
-
Martin, M.1
Geffner, H.2
-
37
-
-
0000640432
-
Inductive logic programming
-
Muggleton, S. (1991). Inductive logic programming. New Generation Computing, 8(4), 295-318.
-
(1991)
New Generation Computing
, vol.8
, Issue.4
, pp. 295-318
-
-
Muggleton, S.1
-
38
-
-
56449092660
-
An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning
-
Parr, R., Li, L., Taylor, G., Painter-Wakefield, C., & Littman, M. (2008). An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning. In Proceedings of the Twenty-Fifth International Conference on Machine Learning, pp. 752- 759.
-
(2008)
Proceedings of the Twenty-Fifth International Conference on Machine Learning
, pp. 752-759
-
-
Parr, R.1
Li, L.2
Taylor, G.3
Painter-Wakefield, C.4
Littman, M.5
-
39
-
-
34547982545
-
Analyzing feature generation for value-function approximation
-
Parr, R., Painter-Wakefield, C., Li, L., & Littman, M. (2007). Analyzing feature generation for value-function approximation. In Proceedings of the Twenty-Fourth International Conference on Machine Learning, pp. 737-744.
-
(2007)
Proceedings of the Twenty-Fourth International Conference on Machine Learning
, pp. 737-744
-
-
Parr, R.1
Painter-Wakefield, C.2
Li, L.3
Littman, M.4
-
40
-
-
0036927202
-
Greedy linear valueapproximation for factored Markov decision processes
-
Patrascu, R., Poupart, P., Schuurmans, D., Boutilier, C., & Guestrin, C. (2002). Greedy linear valueapproximation for factored Markov decision processes. In Proceedings of the Eighteenth National Conference on Artificial Intelligence, pp. 285-291.
-
(2002)
Proceedings of the Eighteenth National Conference on Artificial Intelligence
, pp. 285-291
-
-
Patrascu, R.1
Poupart, P.2
Schuurmans, D.3
Boutilier, C.4
Guestrin, C.5
-
46
-
-
60549103706
-
Practical solution techniques for first-order MDPs
-
Sanner, S., & Boutilier, C. (2009). Practical solution techniques for first-order MDPs. Artificial Intelligence, 173(5-6), 748-788.
-
(2009)
Artificial Intelligence
, vol.173
, Issue.5-6
, pp. 748-788
-
-
Sanner, S.1
Boutilier, C.2
-
47
-
-
0033901602
-
Convergence results for single-step on-policy reinforcement-learning algorithms
-
Singh, S., Jaakkola, T., Littman, M., & Szepesvari, C. (2000). Convergence results for single-step on-policy reinforcement-learning algorithms. Machine Learning, 38(3), 287-308.
-
(2000)
Machine Learning
, vol.38
, Issue.3
, pp. 287-308
-
-
Singh, S.1
Jaakkola, T.2
Littman, M.3
Szepesvari, C.4
-
48
-
-
33847202724
-
Learning to predict by the methods of temporal differences
-
Sutton, R. S. (1988). Learning to predict by the methods of temporal differences. Machine Learning, 3, 9-44.
-
(1988)
Machine Learning
, vol.3
, pp. 9-44
-
-
Sutton, R.S.1
-
50
-
-
33845344721
-
Learning tetris using the noisy cross-entropy method
-
Szita, I., & Lorincz, A. (2006). Learning tetris using the noisy cross-entropy method. Neural Computation, 18, 2936-2941.
-
(2006)
Neural Computation
, vol.18
, pp. 2936-2941
-
-
Szita, I.1
Lorincz, A.2
-
51
-
-
0029276036
-
Temporal difference learning and TD-Gammon
-
Tesauro, G. (1995). Temporal difference learning and TD-Gammon. Communications of the ACM, 38(3), 58-68.
-
(1995)
Communications of the ACM
, vol.38
, Issue.3
, pp. 58-68
-
-
Tesauro, G.1
-
52
-
-
0031143730
-
An analysis of temporal-difference learning with function approximation
-
Tsitsiklis, J., & Roy, B. V. (1997). An analysis of temporal-difference learning with function approximation. IEEE Transactions on Automatic Control, 42(5), 674-690.
-
(1997)
IEEE Transactions on Automatic Control
, vol.42
, Issue.5
, pp. 674-690
-
-
Tsitsiklis, J.1
Roy, B.V.2
-
53
-
-
0008864313
-
Relative value function approximation
-
University of Massachusetts, Department of Computer Science
-
Utgoff, P. E., & Precup, D. (1997). Relative value function approximation. Tech. rep., University of Massachusetts, Department of Computer Science.
-
(1997)
Tech. Rep.
-
-
Utgoff, P.E.1
Precup, D.2
-
54
-
-
2342555200
-
Constuctive function approximation
-
In Motoda, & Liu (Eds.), Kluwer
-
Utgoff, P. E., & Precup, D. (1998). Constuctive function approximation. In Motoda, & Liu (Eds.), Feature Extraction, Construction, and Selection: A Data-Mining Perspective, pp. 219-235. Kluwer.
-
(1998)
Feature Extraction, Construction, and Selection: A Data-Mining Perspective
, pp. 219-235
-
-
Utgoff, P.E.1
Precup, D.2
-
55
-
-
32144443210
-
Integrating planning and learning: The PRODIGY architecture
-
Veloso, M., Carbonell, J., Perez, A., Borrajo, D., Fink, E., & Blythe, J. (1995). Integrating planning and learning: The PRODIGY architecture. Journal of Experimental and Theoretical AI, 7(1), 81-120.
-
(1995)
Journal of Experimental and Theoretical AI
, vol.7
, Issue.1
, pp. 81-120
-
-
Veloso, M.1
Carbonell, J.2
Perez, A.3
Borrajo, D.4
Fink, E.5
Blythe, J.6
-
57
-
-
0012252296
-
Tight performance bounds on greedy policies based on imperfect value functions
-
Northeastern University
-
Williams, R. J., & Baird, L. C. (1993). Tight performance bounds on greedy policies based on imperfect value functions. Tech. rep., Northeastern University.
-
(1993)
Tech. Rep.
-
-
Williams, R.J.1
Baird, L.C.2
-
59
-
-
58849135844
-
Stochastic enforced hill-climbing
-
Wu, J., Kalyanam, R., & Givan, R. (2008). Stochastic enforced hill-climbing. In Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling, pp. 396-403.
-
(2008)
Proceedings of the Eighteenth International Conference on Automated Planning and Scheduling
, pp. 396-403
-
-
Wu, J.1
Kalyanam, R.2
Givan, R.3
-
60
-
-
26944495251
-
Feature-discovering approximate value iteration methods
-
Wu, J., & Givan, R. (2005). Feature-discovering approximate value iteration methods. In Proceedings of the Symposium on Abstraction, Reformulation, and Approximation, pp. 321-331.
-
(2005)
Proceedings of the Symposium on Abstraction, Reformulation, and Approximation
, pp. 321-331
-
-
Wu, J.1
Givan, R.2
-
61
-
-
13444310066
-
Inductive policy selection for first-order MDPs
-
Yoon, S., Fern, A., & Givan, R. (2002). Inductive policy selection for first-order MDPs. In Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence, pp. 568-576.
-
(2002)
Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence
, pp. 568-576
-
-
Yoon, S.1
Fern, A.2
Givan, R.3
-
62
-
-
58349118462
-
FF-Replan: A baseline for probabilistic planning
-
Yoon, S., Fern, A., & Givan, R. (2007). FF-Replan: A baseline for probabilistic planning. In Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling, pp. 352-358.
-
(2007)
Proceedings of the Seventeenth International Conference on Automated Planning and Scheduling
, pp. 352-358
-
-
Yoon, S.1
Fern, A.2
Givan, R.3
-
63
-
-
31144453572
-
The first probabilistic track of the international planning competition
-
Younes, H., Littman, M., Weissman, D., & Asmuth, J. (2005). The first probabilistic track of the international planning competition. Journal of Artificial Intelligence Research, 24, 851-887.
-
(2005)
Journal of Artificial Intelligence Research
, vol.24
, pp. 851-887
-
-
Younes, H.1
Littman, M.2
Weissman, D.3
Asmuth, J.4
|