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An Introduction to Learning Automata and Optimization

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Advances in Learning Automata and Intelligent Optimization

Abstract

Learning automaton (LA) is one of the reinforcement learning techniques in artificial intelligence. Learning automata’s learning ability in unknown environments is a useful technique for modeling, controlling, and solving many real problems in the distributed and decentralized environments. In this chapter, first, we provide an overview of LA concepts and recent variants of LA models. Then, we present a brief description of the recent reinforcement learning mechanisms for solving optimization problems. Finally, the evolution of the recent LA models for optimization is presented.

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Kazemi Kordestani, J., Razapoor Mirsaleh, M., Rezvanian, A., Meybodi, M.R. (2021). An Introduction to Learning Automata and Optimization. In: Kazemi Kordestani, J., Mirsaleh, M.R., Rezvanian, A., Meybodi, M.R. (eds) Advances in Learning Automata and Intelligent Optimization. Intelligent Systems Reference Library, vol 208. Springer, Cham. https://doi.org/10.1007/978-3-030-76291-9_1

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