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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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發(fā)表于 2025-3-23 12:37:48 | 只看該作者
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發(fā)表于 2025-3-23 15:57:53 | 只看該作者
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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發(fā)表于 2025-3-23 21:51:47 | 只看該作者
https://doi.org/10.1007/978-3-030-53141-6Reinforcement Learning; Learning Automata; Cellular Learning Automata; Wavefront Cellular Learning Aut
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發(fā)表于 2025-3-24 01:29:24 | 只看該作者
978-3-030-53143-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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發(fā)表于 2025-3-24 03:58:39 | 只看該作者
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發(fā)表于 2025-3-24 13:56:14 | 只看該作者
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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發(fā)表于 2025-3-24 18:00:37 | 只看該作者
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發(fā)表于 2025-3-25 00:23:58 | 只看該作者
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
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