Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/493
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dc.contributor.authorBrabazon, Anthony. ;en_US
dc.contributor.authorMcGarraghy, Seeen. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:17:41Z-
dc.date.available2020-05-17T08:17:41Z-
dc.date.issued2018en_US
dc.identifier.isbn9783319591568 ;en_US
dc.identifier.isbn9783319591551 (print) ;en_US
dc.identifier.isbn9783319591575 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/493-
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9783319591551. ;en_US
dc.descriptionQA75.5-76.95 ;en_US
dc.descriptionen_US
dc.descriptionPrinted edition: ; 9783319591575. ;en_US
dc.descriptionen_US
dc.description.abstractThis 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. ;en_US
dc.description.statementofresponsibilityby Anthony Brabazon, Seeen McGarraghy.en_US
dc.description.tableofcontentsIntroduction -- Formal Models of Foraging -- Sensor Modalities -- Individual and Social Learning -- Introduction to Foraging Algorithms -- Mammals -- Bird Foraging Algorithms -- Fish Algorithms -- Ant Foraging Algorithms -- Honeybee Inspired Algorithms -- Bioluminescence Algorithms -- Spider Algorithms -- Worm Algorithm -- Bacteria Inspired Algorithms -- Slime Mould Foraging -- Plant Foraging Algorithms -- Group Search and Predatory Search -- Evolving Foraging Algorithms -- Conclusions. ;en_US
dc.format.extentXVIII, 478 p. ; online resource. ;en_US
dc.publisherSpringer International Publishing :en_US
dc.publisherImprint: Springer,en_US
dc.relation.ispartofseriesNatural Computing Series, ; 1619-7127. ;en_US
dc.relation.ispartofseriesNatural Computing Series, ; 1619-7127. ;en_US
dc.relation.haspart9783319591551.pdfen_US
dc.subjectInformation theory. ;en_US
dc.subjectEngineeringen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectOperations research. ;en_US
dc.subjectTheory of Computation. ; http://scigraph.springernature.com/things/product-market-codes/I16005. ;en_US
dc.subjectComputational Intelligence. ; http://scigraph.springernature.com/things/product-market-codes/T11014. ;en_US
dc.subjectArtificial Intelligence and Roboticsen_US
dc.subjectOperations Research, Management Science. ; http://scigraph.springernature.com/things/product-market-codes/M26024. ;en_US
dc.subjectOperations Research/Decision Theory. ; http://scigraph.springernature.com/things/product-market-codes/521000. ;en_US
dc.subject.ddc004.0151 ; 23 ;en_US
dc.titleForaging-Inspired Optimisation Algorithmsen_US
dc.typeBooken_US
dc.publisher.placeCham :en_US
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
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9783319591551.pdf7.8 MBAdobe PDFThumbnail
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Full metadata record
DC FieldValueLanguage
dc.contributor.authorBrabazon, Anthony. ;en_US
dc.contributor.authorMcGarraghy, Seeen. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:17:41Z-
dc.date.available2020-05-17T08:17:41Z-
dc.date.issued2018en_US
dc.identifier.isbn9783319591568 ;en_US
dc.identifier.isbn9783319591551 (print) ;en_US
dc.identifier.isbn9783319591575 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/493-
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9783319591551. ;en_US
dc.descriptionQA75.5-76.95 ;en_US
dc.descriptionen_US
dc.descriptionPrinted edition: ; 9783319591575. ;en_US
dc.descriptionen_US
dc.description.abstractThis 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. ;en_US
dc.description.statementofresponsibilityby Anthony Brabazon, Seeen McGarraghy.en_US
dc.description.tableofcontentsIntroduction -- Formal Models of Foraging -- Sensor Modalities -- Individual and Social Learning -- Introduction to Foraging Algorithms -- Mammals -- Bird Foraging Algorithms -- Fish Algorithms -- Ant Foraging Algorithms -- Honeybee Inspired Algorithms -- Bioluminescence Algorithms -- Spider Algorithms -- Worm Algorithm -- Bacteria Inspired Algorithms -- Slime Mould Foraging -- Plant Foraging Algorithms -- Group Search and Predatory Search -- Evolving Foraging Algorithms -- Conclusions. ;en_US
dc.format.extentXVIII, 478 p. ; online resource. ;en_US
dc.publisherSpringer International Publishing :en_US
dc.publisherImprint: Springer,en_US
dc.relation.ispartofseriesNatural Computing Series, ; 1619-7127. ;en_US
dc.relation.ispartofseriesNatural Computing Series, ; 1619-7127. ;en_US
dc.relation.haspart9783319591551.pdfen_US
dc.subjectInformation theory. ;en_US
dc.subjectEngineeringen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectOperations research. ;en_US
dc.subjectTheory of Computation. ; http://scigraph.springernature.com/things/product-market-codes/I16005. ;en_US
dc.subjectComputational Intelligence. ; http://scigraph.springernature.com/things/product-market-codes/T11014. ;en_US
dc.subjectArtificial Intelligence and Roboticsen_US
dc.subjectOperations Research, Management Science. ; http://scigraph.springernature.com/things/product-market-codes/M26024. ;en_US
dc.subjectOperations Research/Decision Theory. ; http://scigraph.springernature.com/things/product-market-codes/521000. ;en_US
dc.subject.ddc004.0151 ; 23 ;en_US
dc.titleForaging-Inspired Optimisation Algorithmsen_US
dc.typeBooken_US
dc.publisher.placeCham :en_US
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9783319591551.pdf7.8 MBAdobe PDFThumbnail
Preview File
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBrabazon, Anthony. ;en_US
dc.contributor.authorMcGarraghy, Seeen. ;en_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-05-17T08:17:41Z-
dc.date.available2020-05-17T08:17:41Z-
dc.date.issued2018en_US
dc.identifier.isbn9783319591568 ;en_US
dc.identifier.isbn9783319591551 (print) ;en_US
dc.identifier.isbn9783319591575 (print) ;en_US
dc.identifier.urihttp://localhost/handle/Hannan/493-
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionen_US
dc.descriptionSpringerLink (Online service) ;en_US
dc.descriptionPrinted edition: ; 9783319591551. ;en_US
dc.descriptionQA75.5-76.95 ;en_US
dc.descriptionen_US
dc.descriptionPrinted edition: ; 9783319591575. ;en_US
dc.descriptionen_US
dc.description.abstractThis 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. ;en_US
dc.description.statementofresponsibilityby Anthony Brabazon, Seeen McGarraghy.en_US
dc.description.tableofcontentsIntroduction -- Formal Models of Foraging -- Sensor Modalities -- Individual and Social Learning -- Introduction to Foraging Algorithms -- Mammals -- Bird Foraging Algorithms -- Fish Algorithms -- Ant Foraging Algorithms -- Honeybee Inspired Algorithms -- Bioluminescence Algorithms -- Spider Algorithms -- Worm Algorithm -- Bacteria Inspired Algorithms -- Slime Mould Foraging -- Plant Foraging Algorithms -- Group Search and Predatory Search -- Evolving Foraging Algorithms -- Conclusions. ;en_US
dc.format.extentXVIII, 478 p. ; online resource. ;en_US
dc.publisherSpringer International Publishing :en_US
dc.publisherImprint: Springer,en_US
dc.relation.ispartofseriesNatural Computing Series, ; 1619-7127. ;en_US
dc.relation.ispartofseriesNatural Computing Series, ; 1619-7127. ;en_US
dc.relation.haspart9783319591551.pdfen_US
dc.subjectInformation theory. ;en_US
dc.subjectEngineeringen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectOperations research. ;en_US
dc.subjectTheory of Computation. ; http://scigraph.springernature.com/things/product-market-codes/I16005. ;en_US
dc.subjectComputational Intelligence. ; http://scigraph.springernature.com/things/product-market-codes/T11014. ;en_US
dc.subjectArtificial Intelligence and Roboticsen_US
dc.subjectOperations Research, Management Science. ; http://scigraph.springernature.com/things/product-market-codes/M26024. ;en_US
dc.subjectOperations Research/Decision Theory. ; http://scigraph.springernature.com/things/product-market-codes/521000. ;en_US
dc.subject.ddc004.0151 ; 23 ;en_US
dc.titleForaging-Inspired Optimisation Algorithmsen_US
dc.typeBooken_US
dc.publisher.placeCham :en_US
Appears in Collections:مدیریت فناوری اطلاعات

Files in This Item:
File Description SizeFormat 
9783319591551.pdf7.8 MBAdobe PDFThumbnail
Preview File