The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Variable Resolution Discretization in Optimal Control
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Cites
Markov decision processes: Discrete stochastic dynamic programming
Hazeghi, K., & Puterman, M. L. (1995) · Journal of the American Statistical Association · doi:10.2307/2291177 · Cited by 8,037
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Puterman, M. L. (1994) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316887 · Cited by 6,024
User’s guide to viscosity solutions of second order partial differential equations
Crandall, M. G., Ishii, H., & Lions, P.-L. (1992) · Bulletin of the American Mathematical Society · doi:10.1090/s0273-0979-1992-00266-5 · Cited by 4,781
Fast Learning in Networks of Locally-Tuned Processing Units
Moody, J., & Darken, C. J. (1989) · Neural Computation · doi:10.1162/neco.1989.1.2.281 · Cited by 4,194
(2012) · Encyclopedia of the Sciences of Learning · doi:10.1007/978-1-4419-1428-6_5086 · Cited by 3,515
Neuronlike adaptive elements that can solve difficult learning control problems
Barto, A. G., Sutton, R. S., & Anderson, C. W. (1983) · IEEE Transactions on Systems, Man, and Cybernetics · doi:10.1109/tsmc.1983.6313077 · Cited by 3,233
Random Number Generation and Quasi-Monte Carlo Methods.
Collings, B. J., & Niederreiter, H. (1993) · Journal of the American Statistical Association · doi:10.2307/2290359 · Cited by 2,884
An Algorithm for Finding Best Matches in Logarithmic Expected Time
Friedman, J. H., Bentley, J. L., & Finkel, R. A. (1977) · ACM Transactions on Mathematical Software · doi:10.1145/355744.355745 · Cited by 2,813
Random Number Generation and Quasi-Monte Carlo Methods
Niederreiter, H. (1992) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611970081 · Cited by 2,770
Controlled Markov Processes and Viscosity Solutions
(2006) · Stochastic Modelling and Applied Probability · doi:10.1007/0-387-31071-1 · Cited by 2,684
Cited by
A Comprehensive Survey of Multiagent Reinforcement Learning
Busoniu, L., Babuska, R., & De Schutter, B. (2008) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2007.913919 · Cited by 2,235
Deep Reinforcement Learning: A Survey
Wang, X., Wang, S., Liang, X., Zhao, D., Huang, J., Xu, X., Dai, B., & Miao, Q. (2024) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2022.3207346 · Cited by 972
Finding approximate POMDP solutions through belief compression
Roy, N., Gordon, G., & Thrun, S. (2005) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1496 · Cited by 254
Metadata
- Authors
- Munos, R., & Moore, A.
- Venue
- Machine Learning
- Published
- 2002-11
- Volume
- 49
- Issue
- 2-3
- Pages
- 291-323
- ISSN
- 0885-6125 (ISSN-L)
- 1573-0565
- OpenAlex
- W1552830313
- Cited by
- 321
- References
- 43
- FWCI
- 15.39
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Munos, R., & Moore, A. (2002). Variable Resolution Discretization in Optimal Control. Machine Learning. https://doi.org/10.1023/a%3A1017992615625
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
