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Recent Advances in Learning Automata
Alireza Rezvanian
Ali Mohammad Saghiri
Seyed Mehdi Vahidipour
Mehdi Esnaashari
Mohammad Reza Meybodi
出版
Springer
, 2018-01-17
主題
Computers / Artificial Intelligence / General
Technology & Engineering / Engineering (General)
Technology & Engineering / General
ISBN
3319724282
9783319724287
URL
http://books.google.com.hk/books?id=k8FHDwAAQBAJ&hl=&source=gbs_api
EBook
SAMPLE
註釋
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.