Ali Mohammad Saghiri, M. Daliri Khomami, Mohammad Reza Meybodi.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
Cham, Switzerland :
Name of Publisher, Distributor, etc.
Springer,
Date of Publication, Distribution, etc.
[2019]
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
1 online resource (62 pages)
SERIES
Series Title
SpringerBriefs in Applied Sciences and Technology
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references.
CONTENTS NOTE
Text of Note
Random walk algorithms: Definitions, weaknesses, and learning automata based approach -- Intelligent Models of Random Walk -- Applications -- Conclusions.
0
SUMMARY OR ABSTRACT
Text of Note
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.
OTHER EDITION IN ANOTHER MEDIUM
Title
Intelligent Random Walk: an Approach Based on Learning Automata.