Intelligent Random Walk: An Approach Based on Learning Automata

Nonfiction, Science & Nature, Technology, Robotics, Computers, Advanced Computing, Artificial Intelligence, General Computing
Cover of the book Intelligent Random Walk: An Approach Based on Learning Automata by Ali Mohammad Saghiri, M. Daliri Khomami, Mohammad Reza Meybodi, Springer International Publishing
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Author: Ali Mohammad Saghiri, M. Daliri Khomami, Mohammad Reza Meybodi ISBN: 9783030108830
Publisher: Springer International Publishing Publication: January 2, 2019
Imprint: Springer Language: English
Author: Ali Mohammad Saghiri, M. Daliri Khomami, Mohammad Reza Meybodi
ISBN: 9783030108830
Publisher: Springer International Publishing
Publication: January 2, 2019
Imprint: Springer
Language: English

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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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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