Advances in Learning Automata and Intelligent Optimization (eBook)

Javidan Kazemi Kordestani, Mehdi Razapoor Mirsaleh, Alireza Rezvanian, Mohammad Reza Meybodi (Herausgeber)

eBook Download: PDF

2021
340 Seiten
Springer International Publishing (Verlag)
978-3-030-76291-9 (ISBN)

Infos

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. 

Produkt-Details

• Erscheint lt. Verlag: 23.6.2021
• Reihe/Serie: Intelligent Systems Reference Library
• Reihe/Serie: Intelligent Systems Reference Library
• Zusatzinfo: XX, 340 p. 153 illus., 151 illus. in color.
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Technik ► Bauwesen
• Schlagworte: Cellular Learning Automata • Differential evolution • Distributed Learning Automata • Dynamic Optimization Problems • evolutionary optimization • Function Evaluation Management • Interconnected Learning Automata • learning automata • Memetic Algorithms • Multi-Population Methods • Network of Learning Automata • Object Migration Automaton • Parameter Control • Particle swarm optimization • Reinforcement Learning
• ISBN-10: 3-030-76291-2 / 3030762912
• ISBN-13: 978-3-030-76291-9 / 9783030762919