Cellular Learning Automata: Theory and Applications (Hardcover, 1st ed. 2021)

This book highlights both theoretical and applied advances in cellular learning automata (CLA), a type of hybrid computational model that has been successfully employed in various areas to solve complex problems and to model, learn, or simulate complicated patterns of behavior. Owing to CLA's parallel and learning abilities, it has proven to be quite effective in uncertain, time-varying, decentralized, and distributed environments. The book begins with a brief introduction to various CLA models, before focusing on recently developed CLA variants. In turn, the research areas related to CLA are addressed as bibliometric network analysis perspectives. The next part of the book presents CLA-based solutions to several computer science problems in e.g. static optimization, dynamic optimization, wireless networks, mesh networks, and cloud computing. Given its scope, the book is well suited for all researchers in the fields of artificial intelligence and reinforcement learning.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Systems, Decision and Control, 307
Release date:	July 2020
First published:	2021
Authors:	Reza Vafashoar • Hossein Morshedlou • Alireza Rezvanian • Mohammad Reza Meybodi
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	365
Edition:	1st ed. 2021
ISBN-13:	978-3-03-053140-9
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	3-03-053140-6
Barcode:	9783030531409

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