Socially guided intrinsic motivation for robot learning of motor skills

This paper presents a technical approach to robot learning of motor skills which combines active intrinsically motivated learning with imitation learning. Our algorithmic architecture, called SGIM-D , allows efficient learning of high-dimensional continuous sensorimotor inverse models in robots, and...

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Veröffentlicht in:	Autonomous robots Jg. 36; H. 3; S. 273 - 294
Hauptverfasser:	Nguyen, Sao Mai, Oudeyer, Pierre-Yves
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Boston Springer US 01.03.2014 Springer Nature B.V Springer Verlag
Schlagworte:	Algorithms Architecture Artificial Intelligence Cognitive science Computer Imaging Computer Science Control Engineering Inverse Learning Machine Learning Mechatronics Motivation Motor ability Motors Parameterization Pattern Recognition and Graphics Policies Robot arms Robot learning Robotics Robotics and Automation Robots Skills Vision Intrinsic motivation Inverse model Active learning Motor skill learning Imitation Exploration Programming by demonstration Learning from demonstration Inverse Model Intrinsic Motivation Motor Skill Learning Learning from Demonstration Programming by Demonstration Active Learning
ISSN:	0929-5593, 1573-7527
Online-Zugang:	Volltext
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