| 書目名稱 | Foraging-Inspired Optimisation Algorithms | | 編輯 | Anthony Brabazon,Seán McGarraghy | | 視頻video | http://file.papertrans.cn/346/345250/345250.mp4 | | 概述 | Understanding foraging strategies improves search processes.No prior knowledge of natural computing assumed.Valuable for graduate students, academics and practitioners in computer science, informatics | | 叢書名稱 | Natural Computing Series | | 圖書封面 |  | | 描述 | .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.. | | 出版日期 | Book 2018 | | 關(guān)鍵詞 | Foraging; Social Learning; Foraging Algorithms; Animal Behavior; Ant Foraging Algorithm; Bioluminescence | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-59156-8 | | isbn_softcover | 978-3-030-09640-3 | | isbn_ebook | 978-3-319-59156-8Series ISSN 1619-7127 Series E-ISSN 2627-6461 | | issn_series | 1619-7127 | | copyright | Springer Nature Switzerland AG 2018 |
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