Articles liés à Recent Advances in Robot Learning: Machine Learning
Synopsis
Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation.
While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems.
- Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution.
- Since robot learning involves decision making, there is an inherent active learning issue.
- Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data.
- Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints.
These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning.
On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution.
Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
- ÉditeurSpringer
- Date d'édition2011
- ISBN 10 1461380642
- ISBN 13 9781461380641
- ReliureBroché
- Langueanglais
- Nombre de pages228
- ÉditeurFranklin Judy A., Mitchell Tom M., Thrun Sebastian
- Coordonnées du fabricantnon disponible
Acheter neuf
Afficher cet article
EUR 136,16
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délaisAutres éditions populaires du même titre
Résultats de recherche pour Recent Advances in Robot Learning: Machine Learning
Image fournie par le vendeur
Recent Advances in Robot Learning
impression à la demandeVendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning . N° de réf. du vendeur 4196173
Quantité disponible : Plus de 20 disponibles
Image d'archives
Recent Advances in Robot Learning: Machine Learning (The Springer International Series in Engineering and Computer Science)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In. N° de réf. du vendeur ria9781461380641_new
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Recent Advances in Robot Learning
Edité par
Springer US, Springer New York Sep 2011, 2011
ISBN 10 : 1461380642
ISBN 13 : 9781461380641
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3).Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 228 pp. Englisch. N° de réf. du vendeur 9781461380641
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Recent Advances in Robot Learning : Machine Learning
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3). N° de réf. du vendeur 9781461380641
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Recent Advances in Robot Learning
impression à la demandeVendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being applied to many subproblems in robot perception and control, often with objectives as diverse as parameter calibration and concept formulation. While no unified robot learning framework has yet emerged to cover the variety of problems and approaches described in these papers and other publications, a clear set of shared issues underlies many robot learning problems. Machine learning, when applied to robotics, is situated: it is embedded into a real-world system that tightly integrates perception, decision making and execution. Since robot learning involves decision making, there is an inherent active learning issue. Robotic domains are usually complex, yet the expense of using actual robotic hardware often prohibits the collection of large amounts of training data. Most robotic systems are real-time systems. Decisions must be made within critical or practical time constraints. These characteristics present challenges and constraints to the learning system. Since these characteristics are shared by other important real-world application domains, robotics is a highly attractive area for research on machine learning. On the other hand, machine learning is also highly attractive to robotics. There is a great variety of open problems in robotics that defy a static, hand-coded solution. Recent Advances in Robot Learning is an edited volume of peer-reviewed original research comprising seven invited contributions by leading researchers. This research work has also been published as a special issue of Machine Learning (Volume 23, Numbers 2 and 3). 228 pp. Englisch. N° de réf. du vendeur 9781461380641
Quantité disponible : 2 disponible(s)
Image d'archives
Recent Advances in Robot Learning: Machine Learning (The Springer International Series in Engineering and Computer Science)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur ABLIING23Mar2716030034475
Quantité disponible : Plus de 20 disponibles
Image d'archives
Recent Advances in Robot Learning
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. pp. iv + 218. N° de réf. du vendeur 2658588236
Quantité disponible : 4 disponible(s)
Image d'archives
Recent Advances in Robot Learning
impression à la demandeVendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Print on Demand pp. iv + 218. N° de réf. du vendeur 51004307
Quantité disponible : 4 disponible(s)
Image d'archives
Recent Advances in Robot Learning: Machine Learning
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Paperback. Etat : Brand New. reprint edition. 224 pages. 9.13x6.10x0.59 inches. In Stock. N° de réf. du vendeur x-1461380642
Quantité disponible : 2 disponible(s)
Image d'archives
Recent Advances in Robot Learning
impression à la demandeVendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. PRINT ON DEMAND pp. iv + 218. N° de réf. du vendeur 1858588230
Quantité disponible : 4 disponible(s)