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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Advances in Learning Automata and Intelligent Optimization

Advances in Learning Automata and Intelligent Optimization

Kazemi Kordestani, Javidan
Mirsaleh, Mehdi Razapoor
Rezvanian, Alireza

Hardcover

Series: Intelligent Systems Reference Library, Book 208

Technology & EngineeringGeneral Computers

ISBN10: 3030762904
ISBN13: 9783030762902
Publisher: Springer Nature
Published: Jun 24 2021
Pages: 340
Weight: 1.50
Height: 0.81 Width: 6.14 Depth: 9.21
Language: English
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.

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