Recent Advances in Learning Automata

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, especial...

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Detaylı Bibliyografya
Asıl Yazarlar: Rezvanian, Alireza (Yazar), Saghiri, Ali Mohammad (Yazar), Vahidipour, Seyed Mehdi (Yazar), Esnaashari, Mehdi (Yazar), Meybodi, Mohammad Reza (Yazar)
Müşterek Yazar: SpringerLink (Online service)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer International Publishing : 2018.
Imprint: Springer,
Edisyon:1st ed. 2018.
Seri Bilgileri:Studies in Computational Intelligence, 754
Konular:
Computational intelligence.
Artificial intelligence.
Computational Intelligence.
Artificial Intelligence.
Online Erişim:Full-text access
Diğer Bilgiler
Özet: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.
Fiziksel Özellikler:XIX, 458 p. 240 illus., 126 illus. in color. online resource.
ISBN:9783319724287
ISSN:1860-9503 ;
DOI:10.1007/978-3-319-72428-7

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