Cellular Learning Automata: Theory and Applications
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Beschreibung
This book highlights both theoretical and applied advances in cellular learning automata (CLA), a type of hybrid computational model that has been successfully employed in various areas to solve complex problems and to model, learn, or simulate complicated patterns of behavior. Owing to CLA’s parallel and learning abilities, it has proven to be quite effective in uncertain, time-varying, decentralized, and distributed environments.
The book begins with a brief introduction to various CLA models, before focusing on recently developed CLA variants. In turn, the research areas related to CLA are addressed as bibliometric network analysis perspectives. The next part of the book presents CLA-based solutions to several computer science problems in e.g. static optimization, dynamic optimization, wireless networks, mesh networks, and cloud computing. Given its scope, the book is well suited for all researchers in the fields of artificial intelligence and reinforcement learning.
This book highlights both theoretical and applied advances in cellular learning automata (CLA), a type of hybrid computational model that has been successfully employed in various areas to solve complex problems and to model, learn, or simulate complicated patterns of behavior. Owing to CLA’s parallel and learning abilities, it has proven to be quite effective in uncertain, time-varying, decentralized, and distributed environments.
The book begins with a brief introduction to various CLA models, before focusing on recently developed CLA variants. In turn, the research areas related to CLA are addressed as bibliometric network analysis perspectives. The next part of the book presents CLA-based solutions to several computer science problems in e.g. static optimization, dynamic optimization, wireless networks, mesh networks, and cloud computing. Given its scope, the book is well suited for all researchers in the fields of artificial intelligence and reinforcement learning.
Presents recent advances and developments in cellular learning automata Addresses key topics and issues regarding the models, theories, algorithms, and applications of cellular learning automata Highlights recent application areas of cellular learning automata including image processing, data mining, wireless sensor networks, peer-to-peer networks, grid computing, cloud computing, social network analysis, cellular networks, and optimization
Autor*in
Reza Vafashoar
Themen in »Cellular Learning Automata: Theory and Applications«
Reinforcement Learning Learning Automata Cellular Learning Automata Wavefront Cellular Learning Automata Dynamic Cellular Learning Automata Irregular Cellular Learning Automata Asynchronous Cellular Learning Automata Network of Learning Automata Discretized Learning Automata Estimator Learning Automata Interconnected Learning Automata Games of Learning Automata Distributed Learning Automata