Foraging-Inspired Optimisation Algorithms
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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.
Understanding foraging strategies improves search processesNo prior knowledge of natural computing assumedValuable for graduate students, academics and practitioners in computer science, informatics, data science, and management science
Understanding foraging strategies improves search processes No prior knowledge of natural computing assumed Valuable for graduate students, academics and practitioners in computer science, informatics, data science, and management science
Autor*in
Anthony Brabazon
Themen in »Foraging-Inspired Optimisation Algorithms«
Foraging Social Learning Foraging Algorithms Animal Behavior Ant Foraging Algorithm Bioluminescence Algorithms Bacteria Inspired Algorithms Chemotaxis Optimization Search Learning Natural Computing Genetic Programming Evolutionary Computing Slime Mould