Intelligent Random Walk: An Approach Based on Learning Automata

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.

List of contents

Random walk algorithms: Definitions, weaknesses, and learning automata based approach.- Intelligent Models of Random Walk.- Applications.- Conclusions.

Summary

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.

Product details

• Authors: M Dalir Khomami, M Daliri Khomami, M. Daliri Khomami, Mojtaba Daliri Khomami, M Meybodi, Mohammad Reza Meybodi, Ali Mohamma Saghiri, Ali Mohammad Saghiri
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 01.01.2019
• EAN: 9783030108823
• ISBN: 978-3-0-3010882-3
• No. of pages: 55
• Dimensions: 155 mm x 4 mm x 235 mm
• Weight: 124 g
• Illustrations: IX, 55 p. 31 illus., 16 illus. in color.
• Series: SpringerBriefs in Applied Sciences and Technology; SpringerBriefs in Computational Intelligence; SpringerBriefs in Applied Sciences and Technology; SpringerBriefs in Computational Intelligence
• Subjects: Natural sciences, medicine, IT, technology > Technology > General, dictionaries; C, Regelungstechnik, machine learning, Maschinelles Lernen, Robotics, Automation, Mathematische Modellierung, engineering, Computational Intelligence, Mathematical modelling, Control, Robotics, Automation, Robotics and Automation, Automatic control engineering, Neural networks (Computer science)