The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
A survey of point-based POMDP solvers
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Citations
Cites
Reinforcement Learning: An Introduction
Sutton, R. S., & Barto, A. G. (1998) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.1998.712192 · Cited by 27,225
Reinforcement Learning: An Introduction
(2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 24,496
Bellman, R. E. (2010) · doi:10.1515/9781400835386 · Cited by 14,588
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
Introduction to Reinforcement Learning
Sutton, R. S., & Barto, A. G. (1998) · The MIT Press eBooks · Cited by 6,855
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
Planning and acting in partially observable stochastic domains
Kaelbling, L. P., Littman, M. L., & Cassandra, A. R. (1998) · Artificial Intelligence · doi:10.1016/s0004-3702(98)00023-x · Cited by 4,149
Dynamic Programming and Markov Processes.
Freimer, M., & Howard, R. A. (1961) · Journal of the American Statistical Association · doi:10.2307/2282268 · Cited by 3,378
Bellman, R. (1957) · Indiana University Mathematics Journal · doi:10.1512/iumj.1957.6.56038 · Cited by 2,408
Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping
Ng, A. Y., Harada, D., & Russell, S. (1999) · Cited by 1,744
Cited by
A probabilistic graphical model foundation for enabling predictive digital twins at scale
Kapteyn, M. G., Pretorius, J. V. R., & Willcox, K. E. (2021) · Nature Computational Science · doi:10.1038/s43588-021-00069-0 · Cited by 346
Intention-aware online POMDP planning for autonomous driving in a crowd
Bai, H., Cai, S., Ye, N., Hsu, D., & Lee, W. S. (2015) · 2015 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2015.7139219 · Cited by 321
Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges
Lei, L., Tan, Y., Zheng, K., Liu, S., Zhang, K., & Shen, X. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2988367 · Cited by 298
Interactive perception: Leveraging action in perception and perception in action
Bohg, J., Hausman, K., Sankaran, B., Brock, O., Kragic, D., Schaal, S., & Sukhatme, G. S. (2017) · IEEE Transactions on Robotics · doi:10.1109/tro.2017.2721939 · Cited by 227
Memory-based control with recurrent neural networks
Heess, N., Hunt, J. J., Lillicrap, T. P., & Silver, D. (2015) · arXiv · doi:10.48550/arxiv.1512.04455 · Cited by 211
Metadata
- Authors
- Shani, G., Pineau, J., & Kaplow, R.
- Venue
- Autonomous Agents and Multi-Agent Systems
- Published
- 2012-06-08
- Volume
- 27
- Issue
- 1
- Pages
- 1-51
- ISSN
- 1387-2532 (ISSN-L)
- 1573-7454
- OpenAlex
- W2055921164
- Cited by
- 422
- References
- 63
- FWCI
- 26.28
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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How to cite
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- CoChat. (2026). Citation check: A survey of point-based POMDP solvers. https://app.cochat.ai/papers/10.1007/s10458-012-9200-2
- The paper
- Shani, G., Pineau, J., & Kaplow, R. (2013). A survey of point-based POMDP solvers. Autonomous Agents and Multi-Agent Systems. https://doi.org/10.1007/s10458-012-9200-2
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.
