Recent Advances in Learning Automata
- Responsibility
- by Alireza Rezvanian, Ali Mohammad Saghiri, Seyed Mehdi Vahidipour, Mehdi Esnaashari, Mohammad Reza Meybodi.
- Digital
- text file; PDF
- Publication
- Cham : Springer International Publishing : Imprint : Springer, 2018.
- Physical description
- 1 online resource (XIX, 458 pages 240 illustrations, 126 illustrations in color.) : online resource
- Series
- Studies in computational intelligence ; 754. 1860-949X
Online
Available online
More options
Description
Creators/Contributors
- Author/Creator
- Rezvanian, Alireza., author.
- Contributor
- Saghiri, Ali Mohammad., author.
- Vahidipour, Seyed Mehdi., author.
- Esnaashari, Mehdi., author.
- Meybodi, Mohammad Reza., author.
Contents/Summary
- Bibliography
- Includes bibliographical references.
- 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.
- (source: Nielsen Book Data)
- Publisher's 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.
(source: Nielsen Book Data)
Subjects
Bibliographic information
- Publication date
- 2018
- Series
- Studies in Computational Intelligence, 1860-949X ; 754
- In
- Springer eBooks
- ISBN
- 9783319724287
- 3319724282
- 9783319724270
- 3319724274
- DOI
- 10.1007/978-3-319-72428-7
