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Foraging-Inspired Optimisation Algorithms

Seán McGarraghy, Anthony Brabazon

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik

Beschreibung

This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organisms, and they then discuss algorithms based on formal models of foraging, how to evolve a foraging strategy, and likely future developments.

No prior knowledge of natural computing is assumed. This book will be of particular interest to graduate students, academics and practitioners in computer science, informatics, data science, management science, and other application domains.

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Schlagwörter

Foraging, Chemotaxis, Social Learning, Honeybees, Group Search, Search, Animal Behavior, Slime Mould, Heuristics, Plant Foraging, Bioluminescence Algorithms, Learning, Evolutionary Computing, Optimization, Natural Computing, Ant Foraging Algorithm, Foraging Algorithms, Bacteria Inspired Algorithms, Predatory Search, Genetic Programming