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...

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Bibliographic Details
Main Authors: Saghiri, Ali Mohammad (Author), Khomami, M. Daliri (Author), Meybodi, Mohammad Reza (Author)
Corporate Author: SpringerLink (Online service)
Format: e-Book
Language:English
Published: Cham : Springer International Publishing : 2019.
Imprint: Springer,
Edition:1st ed. 2019.
Series:SpringerBriefs in Computational Intelligence,
Subjects:
Computational intelligence.
Control engineering.
Robotics.
Automation.
Machine learning.
Neural networks (Computer science) .
Computational Intelligence.
Control, Robotics, Automation.
Machine Learning.
Mathematical Models of Cognitive Processes and Neural Networks.
Online Access:Full-text access
Description
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.
Physical Description:IX, 55 p. 31 illus., 16 illus. in color. online resource.
ISBN:9783030108830
ISSN:2625-3712
DOI:10.1007/978-3-030-10883-0

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