The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms
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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
Bellman, R. E. (2010) · doi:10.1515/9781400835386 · Cited by 14,588
Watkins, C. J. C. H., & Dayan, P. (1992) · Machine Learning · doi:10.1007/bf00992698 · Cited by 9,083
Reinforcement Learning: A Survey
Kaelbling, L. P., Littman, M. L., & Moore, A. W. (1996) · Journal of Artificial Intelligence Research · doi:10.1613/jair.301 · Cited by 8,972
Self-citationMarkov 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
Learning to predict by the methods of temporal differences
Sutton, R. S. (1988) · Machine Learning · doi:10.1007/bf00115009 · Cited by 5,148
Temporal difference learning and TD-Gammon
Tesauro, G. (1995) · Communications of the ACM · doi:10.1145/203330.203343 · Cited by 1,618 · cited 1×
“…that the approach of using a greedy learning policy has yielded some impressive successes, including the world's finest backgammon-playing program (Tesauro, 1995), and state-of-the-art systems for space shuttle scheduling (Zhang & Dietterich, 1995), elevator control (Crites & Barto, 1996), and…”
Background
Cited by
Asynchronous Methods for Deep Reinforcement Learning
Mnih, V., Badia, A. P., Mirza, M., Graves, A., Lillicrap, T. P., Harley, T., Silver, D., & Kavukcuoglu, K. (2016) · arXiv · doi:10.48550/arxiv.1602.01783 · Cited by 7,132
Addressing Function Approximation Error in Actor-Critic Methods
Fujimoto, S., van Hoof, H., & Meger, D. (2018) · arXiv · doi:10.48550/arxiv.1802.09477 · Cited by 3,650
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
Self-citationA survey of machine learning for big data processing
Qiu, J., Wu, Q., Ding, G., Xu, Y., & Feng, S. (2016) · EURASIP Journal on Advances in Signal Processing · doi:10.1186/s13634-016-0355-x · Cited by 894
Metalearning and neuromodulation
Doya, K. (2002) · Neural Networks · doi:10.1016/s0893-6080(02)00044-8 · Cited by 704
Metadata
- Authors
- Singh, S., Jaakkola, T., Littman, M. L., & Szepesvári, C.
- Venue
- Machine Learning
- Published
- 2000-03
- Volume
- 38
- Issue
- 3
- Pages
- 287-308
- ISSN
- 0885-6125 (ISSN-L)
- 1573-0565
- OpenAlex
- W2150339816
- Cited by
- 609
- References
- 7
- FWCI
- 17.08
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Singh, S., Jaakkola, T., Littman, M. L., & Szepesvári, C. (2000). Convergence Results for Single-Step On-Policy Reinforcement-Learning Algorithms. Machine Learning. https://doi.org/10.1023/a%3A1007678930559
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