Title Recent Advances in Learning Automata / by Alireza Rezvanian, Ali Mohammad Saghiri, Seyed Mehdi Vahidipour, Mehdi Esnaashari, Mohammad Reza Meybodi

Published Cham : Springer International Publishing : Imprint: Springer, 2018

Online access available from: Springer eBooks    View Resource Record

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Description 1 online resource (XIX, 458 pages 240 illustrations, 126 illustrations in color.) : online resource Series Studies in Computational Intelligence, 1860-949X ; 754 Studies in computational intelligence ; 754. 1860-949X Contents Learning automata theory -- Cellular learning automata -- Learning automata for wireless sensor networks -- Learning automata for cognitive Peer-to-peer networks -- Learning automata for Complex Social Networks -- Adaptive petri net based on learning automata -- Summary and future directions Summary 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 Bibliography Includes bibliographical references Subject Artificial intelligence. Computational intelligence. Engineering. Form Electronic book Author Esnaashari, Mehdi, author Meybodi, Mohammad Reza, 1952- author Saghiri, Ali Mohammad, author Vahidipour, Seyed Mehdi, author ISBN 3319724282 9783319724287

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