Kniha Machine Learning for Robotics Jan Peters

Machine Learning for Robotics

Learning Methods for Robot Motor Skills

Autor: Jan Peters
Jazyk: Angličtina
Vazba: Brožovaná
Dostupnost: Skladem u dodavatele
Odesíláme za 9-15 dnů
1 377
Autonomous robots have been a vision of robotics, artificial intelligence, and cognitive sciences. A...

Informace o knize

Autor
Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2008
Stránek
128
EAN
9783639021103
ISBN
363902110X
Enbook ID
06811981
Hmotnost
181
Rozměry
152 x 229 x 7

Kompletní popis

Autonomous robots have been a vision of robotics, artificial intelligence, and cognitive sciences. An important step towards this goal is to create robots that can learn to accomplish amultitude of different tasks triggered by environmental context and higher-level instruction. Early approaches to this goal during the heydays of artificial intelligence research in the late 1980s showed that handcrafted approaches do not suffice and that machine learning is needed. However, off the shelf learning techniques often do not scale into real-time or to the high-dimensional domains of manipulator and humanoid robotics. In this book, we investigate the foundations for a general approach to motor skilllearning that employs domain-specific machine learning methods. A theoretically well-founded general approach to representing the required control structures for task representation and executionis presented along with novel learning algorithms that can be applied in this setting. The resulting framework is shown to work well both in simulation and on real robots.

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