Intelligent Random Walk: An Approach Based on Learning Automata

• Κύριοι συγγραφείς: Saghiri, Ali Mohammad (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Khomami, M. Daliri (http://id.loc.gov/vocabulary/relators/aut), Meybodi, Mohammad Reza (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Έκδοση: 1st ed. 2019.
• Σειρά: SpringerBriefs in Computational Intelligence,
• Θέματα: Computational intelligence.; Robotics.; Automation.; Machine learning.; Neural networks (Computer science) .; Computational Intelligence.; Robotics and Automation.; Machine Learning.; Mathematical Models of Cognitive Processes and Neural Networks.
• Φυσική περιγραφή: IX, 55 p. 31 illus., 16 illus. in color. online resource.
• ISBN: 9783030108830
• ISSN: 2625-3704
• DOI: 10.1007/978-3-030-10883-0

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.