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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| Hlavní autor: | |
|---|---|
| Médium: | Elektronický zdroj E-kniha |
| Jazyk: | angličtina |
| Vydáno: |
Cham :
Springer International Publishing,
2018.
|
| Vydání: | 1st ed. 2018. |
| Edice: | Studies in Computational Intelligence,
754 |
| Témata: | |
| ISBN: | 9783319724287 |
| ISSN: | 1860-949X ; |
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| 020 | |a 9783319724287 | ||
| 024 | 7 | |a 10.1007/978-3-319-72428-7 |2 doi | |
| 035 | |a CVTIDW13412 | ||
| 040 | |a Springer-Nature |b eng |c CVTISR |e AACR2 | ||
| 041 | |a eng | ||
| 100 | 1 | |a Rezvanian, Alireza. |4 aut | |
| 245 | 1 | 0 | |a Recent Advances in Learning Automata |h [electronic resource] / |c by Alireza Rezvanian, Ali Mohammad Saghiri, Seyed Mehdi Vahidipour, Mehdi Esnaashari, Mohammad Reza Meybodi. |
| 250 | |a 1st ed. 2018. | ||
| 260 | 1 | |a Cham : |b Springer International Publishing, |c 2018. | |
| 300 | |a XIX, 458 p. 240 illus., 126 illus. in color. |b online resource. | ||
| 490 | 1 | |a Studies in Computational Intelligence, |x 1860-949X ; |v 754 | |
| 500 | |a Engineering | ||
| 505 | 0 | |a 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. | |
| 516 | |a text file PDF | ||
| 520 | |a 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. | ||
| 650 | 0 | |a Computational intelligence. | |
| 650 | 0 | |a Artificial intelligence. | |
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