Intelligent Random Walk: An Approach Based on Learning Automata (Paperback, 1st ed. 2019)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Computational Intelligence
Release date:	2019
First published:	2019
Authors:	Ali Mohammad Saghiri • M. Daliri Khomami • Mohammad Reza Meybodi
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	55
Edition:	1st ed. 2019
ISBN-13:	978-3-03-010882-3
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	3-03-010882-1
Barcode:	9783030108823

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