A brain-computer interface for high-level remote control of an autonomous, reinforcement-learning-based robotic system for reaching and grasping

Authors:
Thomas Lampe;Lukas D.J. Fiederer;Martin Voelker;Alexander Knorr;Martin Riedmiller;Tonio Ball
Affiliations:
Albert-Ludwigs-University, Freiburg, Germany;Albert-Ludwigs-University, Freiburg, Germany;Albert-Ludwigs-University, Freiburg, Germany;Albert-Ludwigs-University, Freiburg, Germany;Albert-Ludwigs-University, Freiburg, Germany;Albert-Ludwigs-University, Freiburg, Germany
Venue:
Proceedings of the 19th international conference on Intelligent User Interfaces
Year:
2014

Citing 6
Cited 0

A practical Bayesian framework for backpropagation networks

Neural Computation
Introduction to Reinforcement Learning

Introduction to Reinforcement Learning
Spatial filtering and selection of optimized components in four class motor imagery EEG data using independent components analysis

Pattern Recognition Letters
Human brain-teleoperated robot between remote places

ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Neural fitted q iteration – first experiences with a data efficient neural reinforcement learning method

ECML'05 Proceedings of the 16th European conference on Machine Learning
Machine-learning-based coadaptive calibration for brain-computer interfaces

Neural Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract