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Titlebook: Advances in Learning Automata and Intelligent Optimization; Javidan Kazemi Kordestani,Mehdi Razapoor Mirsaleh, Book 2021 The Editor(s) (if

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期刊全稱Advances in Learning Automata and Intelligent Optimization
影響因子2023Javidan Kazemi Kordestani,Mehdi Razapoor Mirsaleh,
視頻videohttp://file.papertrans.cn/149/148676/148676.mp4
發(fā)行地址Provides leading studies in the application of learning automata (LA) along with different heuristics for solving optimization problems.Collects recent advances and developments in learning automata-b
學(xué)科分類Intelligent Systems Reference Library
圖書封面Titlebook: Advances in Learning Automata and Intelligent Optimization;  Javidan Kazemi Kordestani,Mehdi Razapoor Mirsaleh, Book 2021 The Editor(s) (if
影響因子This book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA models for optimization. Afterward, the research areas related to LA and optimization are addressed as bibliometric network analysis. Then, LA‘s application in behavior control in evolutionary computation,?and memetic models of?object migration automata?and cellular learning automata for solving NP hard?problems are considered. Next, an overview of multi-population methods for DOPs, LA‘s application in dynamic optimization problems (DOPs), and the function evaluation management in evolutionary multi-population for DOPs are discussed... Highlighted benefits??.? Presents the latest advances in learning automata-based optimization approaches..? Addresses the memetic models of learning automata for solving NP-hard problems..? Discusses the appli
Pindex Book 2021
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Book 2021lems. The ever-increasing application of the LA as a promising reinforcement learning technique in artificial intelligence makes it necessary to provide scholars, scientists, and engineers with a practical discussion on LA solutions for optimization. The book starts with a brief introduction to LA m
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1868-4394 ects recent advances and developments in learning automata-bThis book is devoted to the leading research in applying learning automaton (LA) and heuristics for solving benchmark and real-world optimization problems. The ever-increasing application of the LA as a promising reinforcement learning tech
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