Recent Advances in Learning Automata

Book Description

This book collects recent theoretical advances and concrete applications of learning automata (LAs) in various areas of , presenting a broad treatment of the 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 science domains, from sensor , to peer-to-peer , to complex social , 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 domains.

Table of Contents

Chapter 1 Learning Automata
Chapter 2 Cellular Learning Automata
Chapter Recent Applications
Chapter 3 Learning Automata For Wireless Sensor Networks
Chapter 4 Learning Automata For Cognitive Peer-To-Peer Networks
Chapter 5 Learning Automata For Complex Social Networks
Chapter 6 Adaptive Petri Net Based On Learning Automata
Chapter 7 Summary And Future Directions

Book Details

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Download from UsersCloudTrue PDF, EPUB19.301/22/2018
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