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Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Recent Advances in Learning Automata
• Autor: Alireza Rezvanian, Ali Mohammad Saghiri, Seyed Mehdi Vahidipour, Mehdi Esnaashari, Mohammad Reza Meybodi
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 458
• EAN: 9783319724270
• ISBN: 3319724274
• ID: 18622685
• Nakladatelství: Springer International Publishing AG
• Hmotnost: 1093 g
• Rozměry: 235 × 155 × 33 mm
• Datum vydání: 26. January 2018

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