Articles liés à Growing Adaptive Machines: Combining Development and...
Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks - Couverture rigide
Synopsis
The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks.
The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a reference for experts. Several contributions provide perspectives and future hypotheses on recent highly successful trains of research, including deep learning, the Hyper NEAT model of developmental neural network design, and a simulation of the visual cortex. Other contributions cover recent advances in the design of bio-inspired artificial neural networks, including the creation of machines for classification, the behavioural control of virtual agents, the desi
gn of virtual multi-component robots and morphologies and the creation of flexible intelligence. Throughout, the contributors share their vast expertise on the means and benefits of creating brain-like machines.This book is appropriate for advanced students and practitioners of artificial intelligence and machine learning.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Acheter neuf
Afficher cet article
EUR 92,27
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délais
Résultats de recherche pour Growing Adaptive Machines: Combining Development and...
Image d'archives
Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks
Edité par
Springer, 2014
ISBN 10 : 3642553362
ISBN 13 : 9783642553363
Ancien ou d'occasion
Couverture rigide
Vendeur : Book Dispensary, Concord, ON, Canada
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : As New. AS NEW hardcover, no marks in text, very clean exterior, appears unused. Book. N° de réf. du vendeur 148778
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Growing Adaptive Machines
Edité par
Springer Berlin Heidelberg, 2014
ISBN 10 : 3642553362
ISBN 13 : 9783642553363
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in Growing Adaptive MachinesPresents development and learning in Artificial Neural NetworksEdited results of the DevLeaNN workshop on development and learning in Artificial Neural Networks held in Paris, October 27-28 2012. N° de réf. du vendeur 5064369
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Growing Adaptive Machines : Combining Development and Learning in Artificial Neural Networks
Edité par
Springer Berlin Heidelberg, 2014
ISBN 10 : 3642553362
ISBN 13 : 9783642553363
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks.The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a reference for experts. Several contributions provide perspectives and future hypotheses on recent highly successful trains of research, including deep learning, the Hyper NEAT model of developmental neural network design, and a simulation of the visual cortex. Other contributions cover recent advances in the design of bio-inspired artificial neural networks, including the creation of machines for classification, the behavioural control of virtual agents, the design of virtual multi-component robots and morphologies and the creation of flexible intelligence. Throughout, the contributors share their vast expertise on the means and benefits of creating brain-like machines.This book is appropriate for advanced students and practitioners of artificial intelligence and machine learning. N° de réf. du vendeur 9783642553363
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Growing Adaptive Machines
Edité par
Springer Berlin Heidelberg Jun 2014, 2014
ISBN 10 : 3642553362
ISBN 13 : 9783642553363
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks.The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a reference for experts. Several contributions provide perspectives and future hypotheses on recent highly successful trains of research, including deep learning, the Hyper NEAT model of developmental neural network design, and a simulation of the visual cortex. Other contributions cover recent advances in the design of bio-inspired artificial neural networks, including the creation of machines for classification, the behavioural control of virtual agents, the design of virtual multi-component robots and morphologies and the creation of flexible intelligence. Throughout, the contributors share their vast expertise on the means and benefits of creating brain-like machines.This book is appropriate for advanced students and practitioners of artificial intelligence and machine learning. 272 pp. Englisch. N° de réf. du vendeur 9783642553363
Quantité disponible : 2 disponible(s)
Image d'archives
Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks (Studies in Computational Intelligence, 557)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In English. N° de réf. du vendeur ria9783642553363_new
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Growing Adaptive Machines
Edité par
Springer Berlin Heidelberg, Springer Berlin Heidelberg Jun 2014, 2014
ISBN 10 : 3642553362
ISBN 13 : 9783642553363
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Neuware -The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks.The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a reference for experts. Several contributions provide perspectives and future hypotheses on recent highly successful trains of research, including deep learning, the Hyper NEAT model of developmental neural network design, and a simulation of the visual cortex. Other contributions cover recent advances in the design of bio-inspired artificial neural networks, including the creation of machines for classification, the behavioural control of virtual agents, the design of virtual multi-component robots and morphologies and the creation of flexible intelligence. Throughout, the contributors share their vast expertise on the means and benefits of creating brain-like machines.This book is appropriate for advanced students and practitioners of artificial intelligence and machine learning.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 272 pp. Englisch. N° de réf. du vendeur 9783642553363
Quantité disponible : 2 disponible(s)
Image d'archives
Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks (Studies in Computational Intelligence)
Edité par
Springer, 2014
ISBN 10 : 3642553362
ISBN 13 : 9783642553363
Ancien ou d'occasion
Couverture rigide
Vendeur : Treehorn Books, Santa Rosa, CA, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : As New. Etat de la jaquette : No Dust Jacket. 9.2 X 6.1 X 0.8 inches; 261 pages. N° de réf. du vendeur 8924
Quantité disponible : 1 disponible(s)
Image d'archives
Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks
Edité par
Springer-Verlag New York Inc, 2014
ISBN 10 : 3642553362
ISBN 13 : 9783642553363
Neuf
Couverture rigide
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : Brand New. 261 pages. 9.75x6.75x0.75 inches. In Stock. N° de réf. du vendeur x-3642553362
Quantité disponible : 2 disponible(s)
Image d'archives
Growing Adaptive Machines: Combining Development and Learning in Artificial Neural Networks (Studies in Computational Intelligence, 557)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur ABLIING23Mar3113020230995
Quantité disponible : Plus de 20 disponibles