Inductive Biases in Machine Learning for Robotics and Control: 156 (Springer Tracts in Advanced Robotics, 156) [Hardcover] [Aug 01, 2023] Lutter, Michael
Language: English
Published by Springer, 2023
- Hardcover
- New

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- Title
- Inductive Biases in Machine Learning for Robotics and Control: 156 (Springer Tracts in Advanced Robotics, 156) [Hardcover] [Aug 01, 2023] Lutter, Michael
- Author
- Lutter, Michael
- Publisher
- Springer
- Publication year
- 2023
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 3031378318
- ISBN 13
- 9783031378317
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 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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From the Back Cover
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 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.
"About the title" may belong to another edition of this title.
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StainesBookHub aim to offer our customers a variety of the old & latest Books. With the Experience of more than 15 Years, we always keep an eye on the latest trends in Books and put our customers' wishes first, we try our best to give books to our customers on lowest prices. We ship Books through Fedex Priority. That is why we have satisfied customers all over the world, and are thrilled to be a part of the Books industry. StainesBooksHub also sell books in Bulk, We try our best to Provied High Quality, Fast Service, Global Shipping.
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We ship Books through Fedex Priority