The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Learning Automata - A Survey
Abstract
Stochastic automata operating in an unknown random environment have been proposed earlier as models of learning. These automata update their action probabilities in accordance with the inputs received from the environment and can improve their own performance during operation. In this context they are referred to as learning automata. A survey of the available results in the area of learning automata has been attempted in this paper. Attention has been focused on the norms of behavior of learning automata, issues in the design of updating schemes, convergence of the action probabilities, and interaction of several automata. Utilization of learning automata in parameter optimization and hypothesis testing is discussed, and potential areas of application are suggested.
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Cites
Pfanzagl, J., & Luce, R. D. (1962) · Econometrica · doi:10.2307/1911299 · Cited by 2,469
Theory of Games and Economic Behavior
Wald, A., Neumann, J. V., & Morgenstern, O. (1947) · The Review of Economics and Statistics · doi:10.2307/1925651 · Cited by 2,329
Stochastic models for learning.
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Gaines, B. R. (1969) · Advances in Information Systems Science · doi:10.1007/978-1-4899-5841-9_2 · Cited by 745
An Introduction to Mathematical Learning Theory
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Markov Processes and Learning Models
(1972) · Mathematics in Science and Engineering/Mathematics in science and engineering · doi:10.1016/s0076-5392(08)x6065-5 · Cited by 307
Adaptation and Learning in Automatic Systems
(1971) · Mathematics in Science and Engineering · doi:10.1016/s0076-5392(08)x6155-7 · Cited by 303
On dimensionality and sample size in statistical pattern classification
Kanal, L. N., & Chandrasekaran, B. (1971) · Pattern Recognition · doi:10.1016/0031-3203(71)90013-6 · Cited by 196
Use of Stochastic Automata for Parameter Self-Optimization with Multimodal Performance Criteria
Shapiro, I., & Narendra, K. S. (1969) · IEEE Transactions on Systems Science and Cybernetics · doi:10.1109/tssc.1969.300228 · Cited by 101
Self-citationThe two-armed-bandit problem with time-invariant finite memory
Cover, T. M., & Hellman, M. E. (1970) · IEEE Transactions on Information Theory · doi:10.1109/tit.1970.1054427 · Cited by 88
Cited by
Reinforcement Learning: An Introduction
(2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2004.842673 · Cited by 24,496
Deep learning in neural networks: an overview
Schmidhuber, J. (2015) · Neural Networks · doi:10.1016/j.neunet.2014.09.003 · Cited by 18,570
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
Boutaba, R., Salahuddin, M. A., Limam, N., Ayoubi, S., Shahriar, N., Estrada-Solano, F., & Caicedo, O. M. (2018) · Journal of Internet Services and Applications · doi:10.1186/s13174-018-0087-2 · Cited by 1,036
Deep Learning for Mobile Multimedia: A Survey
Ota, K., Dao, M. S., Mezaris, V., & Natale, F. G. B. D. (2017) · ACM Transactions on Multimedia Computing, Communications, and Applications · doi:10.1145/3092831 · Cited by 135
Metadata
- Authors
- Narendra, K. S., & Thathachar, M. A. L.
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics
- Published
- 1974-07
- Volume
- SMC-4
- Issue
- 4
- Pages
- 323-334
- ISSN
- 0018-9472 (ISSN-L)
- OpenAlex
- W2064018461
- Cited by
- 668
- References
- 13
- FWCI
- 9.26
- Type
- journal article
- Language
- en
- Open access
- closed
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- Narendra, K. S., & Thathachar, M. A. L. (1974). Learning Automata - A Survey. IEEE Transactions on Systems, Man, and Cybernetics. https://doi.org/10.1109/tsmc.1974.5408453
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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.
