Recent Advances in Learning Automata

Autor: Alireza Rezvanian, Ali Mohammad Saghiri, Seyed Mehdi Vahidipour, Mehdi Esnaashari, Mohammad Reza Meybodi

Jazyk:

Vazba: Brožovaná

Vydavatel: Springer International Publishing AG

Dostupnost: Skladem u dodavatele

Odesíláme za 5-8 dnů

2 286 Kč

This book collects recent theoretical advances and concrete applications of learning automata (LAs)...

Informace o knize

Autor

Alireza Rezvanian, Ali Mohammad Saghiri, Seyed Mehdi Vahidipour, Mehdi Esnaashari, Mohammad Reza Meybodi

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2019

Stránek

458

EAN

9783319891828

Enbook ID

21145353

Vydavatel

Springer International Publishing AG

Hmotnost

730

Rozměry

155 x 235 x 26

Kompletní popis

This book collects recent theoretical advances and concrete applications of learning automata (LAs) in various areas of computer science, presenting a broad treatment of the computer science field in a survey style. Learning automata (LAs) have proven to be effective decision-making agents, especially within unknown stochastic environments. The book starts with a brief explanation of LAs and their baseline variations. It subsequently introduces readers to a number of recently developed, complex structures used to supplement LAs, and describes their steady-state behaviors. These complex structures have been developed because, by design, LAs are simple units used to perform simple tasks; their full potential can only be tapped when several interconnected LAs cooperate to produce a group synergy. In turn, the next part of the book highlights a range of LA-based applications in diverse computer science domains, from wireless sensor networks, to peer-to-peer networks, to complex social networks, and finally to Petri nets. The book accompanies the reader on a comprehensive journey, starting from basic concepts, continuing to recent theoretical findings, and ending in the applications of LAs in problems from numerous research domains. As such, the book offers a valuable resource for all computer engineers, scientists, and students, especially those whose work involves the reinforcement learning and artificial intelligence domains.

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Recent Advances in Learning Automata

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