Description

Book Synopsis

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.



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

Intelligent Random Walk: An Approach Based on

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A Paperback / softback by Ali Mohammad Saghiri, M. Daliri Khomami, Mohammad Reza Meybodi

15 in stock


    View other formats and editions of Intelligent Random Walk: An Approach Based on by Ali Mohammad Saghiri

    Publisher: Springer Nature Switzerland AG
    Publication Date: 14/01/2019
    ISBN13: 9783030108823, 978-3030108823
    ISBN10: 3030108821
    Also in:
    Machine learning Probability and statistics

    Description

    Book Synopsis

    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.



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

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