Intelligent Random Walk : An Approach Based on Learning Automata
Saghiri, Ali Mohammad
Intelligent Random Walk : An Approach Based on Learning Automata by Ali Mohammad Saghiri, M. Daliri Khomami, Mohammad Reza Meybodi. - 1 recurso en línea (IX, 55 páginas) 31 ilustraciones,16 ilustraciones a color - SpringerBriefs in Computational Intelligence 2625-3704 Intelligent Technologies and Robotics (Springer-42732) .
Random walk algorithms: Definitions, weaknesses, and learning automata based approach -- Intelligent Models of Random Walk -- Applications -- Conclusions.
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.
9783030108830
10.1007/978-3-030-10883-0 doi
Markov, Procesos de
QA274.7 / 2019 EB
Intelligent Random Walk : An Approach Based on Learning Automata by Ali Mohammad Saghiri, M. Daliri Khomami, Mohammad Reza Meybodi. - 1 recurso en línea (IX, 55 páginas) 31 ilustraciones,16 ilustraciones a color - SpringerBriefs in Computational Intelligence 2625-3704 Intelligent Technologies and Robotics (Springer-42732) .
Random walk algorithms: Definitions, weaknesses, and learning automata based approach -- Intelligent Models of Random Walk -- Applications -- Conclusions.
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.
9783030108830
10.1007/978-3-030-10883-0 doi
Markov, Procesos de
QA274.7 / 2019 EB