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Books > Computing & IT > Applications of computing > Artificial intelligence
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Advances in Learning Automata and Intelligent Optimization (Hardcover, 1st ed. 2021)
Loot Price: R5,036
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Advances in Learning Automata and Intelligent Optimization (Hardcover, 1st ed. 2021)
Series: Intelligent Systems Reference Library, 208
Expected to ship within 12 - 17 working days
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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 application of learning automata
for behavior control in evolutionary computation in detail. * Gives
the fundamental principles and analyses of the different concepts
associated with multi-population methods for dynamic optimization
problems.
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