Inductive Biases in Machine Learning for Robotics and Control

Name: Inductive Biases in Machine Learning for Robotics and Control
Brand: Springer, Berlin
SKU: 9783031378317
Price: 125.98 EUR
Availability: InStock

Автор: Michael Lutter

Език:

Корици: С твърди корици

Издател: Springer, Berlin

Наличност: Външен склад

Изпращаме след 10-13 дни

125.98 € 246.40 лв

One important robotics problem is "How can one program a robot to perform a task"? Classical robotic...

Информация за книгата

Автор

Michael Lutter

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2023

страници

140

EAN

9783031378317

Enbook ID

43654616

Издател

Springer, Berlin

Теглоt

371

Размери

155 x 235

Пълно описание

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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Inductive Biases in Machine Learning for Robotics and Control

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Пълно описание

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