Description

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.

Intelligent Random Walk: An Approach Based on Learning Automata

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

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This book examines the intelligent random walk algorithms based on learning automata: these versions of random walk algorithms gradually obtain... Read more

    Publisher: Springer Nature Switzerland AG
    Publication Date: 14/01/2019
    ISBN13: 9783030108823, 978-3030108823
    ISBN10: 3030108821

    Number of Pages: 55

    Non Fiction , Computing

    Description

    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.

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