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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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.

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https://doi.org/10.1007/978-3-030-53141-6Reinforcement Learning; Learning Automata; Cellular Learning Automata; Wavefront Cellular Learning Aut

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978-3-030-53143-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Cellular Learning Automata for Collaborative Loss Sharing,oring relations in ICLA. The goal of service providers is to reach a Pareto optimal loss-sharing agreement (LSA). With a Pareto optimal LSA, it is impossible to find another LSA to make utilization of a service provider better off without making at least the utility of one of the service provider’s

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2198-4182 loud computing. Given its scope, the book is well suited for all researchers in the fields of artificial intelligence and reinforcement learning.  .978-3-030-53143-0978-3-030-53141-6Series ISSN 2198-4182 Series E-ISSN 2198-4190