Inductive biases machine learning di lutter michael (19 risultati)
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Inductive Biases in Machine Learning for Robotics and Control (Springer Tracts in Advanced Robotics)
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. pp. 136.
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Inductive Biases in Machine Learning for Robotics and Control | Michael Lutter | Taschenbuch | Springer Tracts in Advanced Robotics | xv | Englisch | 2024 | Springer | EAN 9783031378348 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartma…nn[at]springer[dot]com | Anbieter: preigu.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 134 pages. 9.25x6.10x9.21 inches. In Stock.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 128,39
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - One important robotics problem is 'How can one program a robot to perform a task' Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relies on blac…k-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 128,39
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - One important robotics problem is 'How can one program a robot to perform a task' Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relies on black-box m…odels and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots.
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- Print on Demand
Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer, Berlin, Springer Nature Switzerland, Springer Aug 2024, 2024
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 128,39
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -One important robotics problem is 'How can one program a robot to perform a task' Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solel…y relies on black-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots. 119 pp. Englisch.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 128,39
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -One important robotics problem is 'How can one program a robot to perform a task' Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relie…s on black-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots. 136 pp. Englisch.
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Da: moluna, Greven, Germaniamoluna
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EUR 110,71
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.
Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Switzerland|Springer, 2023
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Da: moluna, Greven, Germaniamoluna
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EUR 109,83
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. One important robotics problem is How can one program a robot to perform a task ? Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot… learning solely relies on black-box .
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 174,85
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Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, Springer International Publishing Aug 2024, 2024
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 128,39
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -One important robotics problem is ¿How can one program a robot to perform a task¿ Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely re…lies on black-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 136 pp. Englisch.
Lingua: Inglese
Editore: Springer, Springer International Publishing Aug 2023, 2023
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 128,39
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Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -One important robotics problem is How can one program a robot to perform a task Classical robotics solves this problem by manually engineering modules for state estimation, planning, and control. In contrast, robot learning solely relies on b…lack-box models and data. This book shows that these two approaches of classical engineering and black-box machine learning are not mutually exclusive. To solve tasks with robots, one can transfer insights from classical robotics to deep networks and obtain better learning algorithms for robotics and control. To highlight that incorporating existing knowledge as inductive biases in machine learning algorithms improves performance, this book covers different approaches for learning dynamics models and learning robust control policies. The presented algorithms leverage the knowledge of Newtonian Mechanics, Lagrangian Mechanics as well as the Hamilton-Jacobi-Isaacs differential equation as inductive bias and are evaluated on physical robots.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 136 pp. Englisch.
Inductive Biases in Machine Learning for Robotics and Control (Springer Tracts in Advanced Robotics)
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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EUR 180,34
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Condizione: New. PRINT ON DEMAND pp. 136.
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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