Titlebook: Cellular Learning Automata: Theory and Applications; Reza Vafashoar,Hossein Morshedlou,Mohammad Reza Me Book 2021 The Editor(s) (if applic

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Invertebrate

隼鷹

https://doi.org/10.1007/978-3-531-92782-4CA) and learning automata (LA). Since CLA has both the computational power of cellular automata and the learning ability of learning automata, it is a useful technique for modeling, controlling, and solving many real problems in the unknown, distributed, and decentralized environments. In this chapt

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Palatial

Michael Stephan,Peter-Paul Grosste the applicability of multi-reinforcement models in channel assignment in multiple collision domains. Next, we propose a method based on multi-reinforcement cellular learning automata for distributed channel assignment in the mesh network.

密碼

https://doi.org/10.1007/978-3-531-92865-4 the users who can benefit insurance coverage depends on the finances of service providers. A cellular learning automaton (CLA) based loss-sharing approach among service providers is considered in this chapter to increase the financial capability of each service provider. ICLA, as an irregular form

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https://doi.org/10.1007/978-3-531-92883-8 solutions for various problems in such systems. By introducing Reinforcement Learning (RL) as an efficient approach in game theory, increasing literature is concerned with the theoretical convergence of RL-based approaches towards Nash equilibrium. Many Q-learning based attempts and multi-agent rei