Name: Inductive Biases in Machine Learning for Robotics and Control (en Inglés)
SKU: 56771601
Price: 121.33 USD
Availability: InStock
Author: Lutter, Michael
ISBN: 9783031378317

portada Inductive Biases in Machine Learning for Robotics and Control (en Inglés)

Inductive Biases in Machine Learning for Robotics and Control (en Inglés)

Formato

Libro Físico

Autor

Michael Lutter

Editorial

Springer

Idioma

Inglés

N° páginas

119

Encuadernación

Tapa Dura

Dimensiones

23.4x15.6x1 cm

Peso

0.37 kg.

ISBN13

9783031378317

Categorías

Ingeniería: general
Robótica

Inductive Biases in Machine Learning for Robotics and Control (en Inglés)

Michael Lutter (Autor) · Springer · Tapa Dura

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Reseña del libro "Inductive Biases in Machine Learning for Robotics and Control (en Inglés)"

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.