Overview
Part of the book series: SpringerBriefs in Applied Sciences and Technology (BRIEFSAPPLSCIENCES)
Part of the book sub series: SpringerBriefs in Computational Intelligence (BRIEFSINTELL)
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Table of contents (4 chapters)
Keywords
About this book
This book examines the intelligent random walk algorithms based on learning automata: these versions of random walk algorithms gradually obtain required information from the nature of the application to improve their efficiency. The book also describes the corresponding applications of this type of random walk algorithm, particularly as an efficient prediction model for large-scale networks such as peer-to-peer and social networks. The book opens new horizons for designing prediction models and problem-solving methods based on intelligent random walk algorithms, which are used for modeling and simulation in various types of networks, including computer, social and biological networks, and which may be employed a wide range of real-world applications.
Authors and Affiliations
Bibliographic Information
Book Title: Intelligent Random Walk: An Approach Based on Learning Automata
Authors: Ali Mohammad Saghiri, M. Daliri Khomami, Mohammad Reza Meybodi
Series Title: SpringerBriefs in Applied Sciences and Technology
DOI: https://doi.org/10.1007/978-3-030-10883-0
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Author(s), under exclusive license to Springer Nature Switzerland AG 2019
Softcover ISBN: 978-3-030-10882-3Published: 14 January 2019
eBook ISBN: 978-3-030-10883-0Published: 02 January 2019
Series ISSN: 2191-530X
Series E-ISSN: 2191-5318
Edition Number: 1
Number of Pages: IX, 55
Number of Illustrations: 15 b/w illustrations, 16 illustrations in colour
Topics: Computational Intelligence, Robotics and Automation, Machine Learning, Mathematical Models of Cognitive Processes and Neural Networks