The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
PAC Bounds for Multi-armed Bandit and Markov Decision Processes
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Citations
Cites
Watkins, C. J. C. H., & Dayan, P. (1992) · Machine Learning · doi:10.1007/bf00992698 · Cited by 9,083
Watkins, C. J. C. H., & Dayan, P. (1992) · Machine Learning · doi:10.1023/a:1022676722315 · Cited by 3,907
(2012) · Encyclopedia of the Sciences of Learning · doi:10.1007/978-1-4419-1428-6_5086 · Cited by 3,515
Asymptotically efficient adaptive allocation rules
Lai, T. L., & Robbins, H. (1985) · Advances in Applied Mathematics · doi:10.1016/0196-8858(85)90002-8 · Cited by 2,406
(2002) · doi:10.1137/s0097539701398375 · Cited by 2,275
Some aspects of the sequential design of experiments
Robbins, H. (1952) · Bulletin of the American Mathematical Society · doi:10.1090/s0002-9904-1952-09620-8 · Cited by 2,184
Neural network learning theoretical foundations
Anthony, M., & Bartlett, P. L. (2009) · Cited by 1,310
Near-Optimal Reinforcement Learning in Polynomial Time
Kearns, M., & Singh, S. (2002) · Machine Learning · doi:10.1023/a:1017984413808 · Cited by 792
Gambling in a rigged casino: The adversarial multi-armed bandit problem
Auer, P., Cesa-Bianchi, N., Freund, Y., & Schapire, R. E. (2002) · Proceedings of IEEE 36th Annual Foundations of Computer Science · doi:10.1109/sfcs.1995.492488 · Cited by 742
Berry, D. A., & Fristedt, B. (1985) · Springer eBooks · doi:10.1007/978-94-015-3711-7 · Cited by 633
Cited by
Algorithms for Reinforcement Learning
Szepesvári, C. (2010) · Synthesis Lectures on Artificial Intelligence and Machine Learning · doi:10.1007/978-3-031-01551-9 · Cited by 1,049
An analysis of model-based Interval Estimation for Markov Decision Processes
Strehl, A. L., & Littman, M. L. (2008) · Journal of Computer and System Sciences · doi:10.1016/j.jcss.2007.08.009 · Cited by 428
Pure Exploration in Multi-armed Bandits Problems
Bubeck, S., Munos, R., & Stoltz, G. (2009) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-04414-4_7 · Cited by 362
Efficient Exploration in Reinforcement Learning
(2012) · SpringerReference · doi:10.1007/springerreference_178956 · Cited by 257
Metadata
- Authors
- Even-Dar, E., Mannor, S., & Mansour, Y.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2002
- Pages
- 255-270
- ISSN
- 0302-9743 (ISSN-L)
- OpenAlex
- W1861050369
- Cited by
- 298
- References
- 23
- FWCI
- 3.05
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: PAC Bounds for Multi-armed Bandit and Markov Decision Processes. https://app.cochat.ai/papers/10.1007/3-540-45435-7_18
- The paper
- Even-Dar, E., Mannor, S., & Mansour, Y. (2002). PAC Bounds for Multi-armed Bandit and Markov Decision Processes. Lecture Notes in Computer Science. https://doi.org/10.1007/3-540-45435-7_18
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.
