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AR
2011
14 years 6 months ago
Imitation Learning of Positional and Force Skills Demonstrated via Kinesthetic Teaching and Haptic Input
A method to learn and reproduce robot force interactions in a Human-Robot Interaction setting is proposed. The method allows a robotic manipulator to learn to perform tasks which ...
Petar Kormushev, Sylvain Calinon, Darwin G. Caldwe...
BMCBI
2010
113views more  BMCBI 2010»
14 years 11 months ago
Improving performance of mammalian microRNA target prediction
Background: MicroRNAs (miRNAs) are single-stranded non-coding RNAs known to regulate a wide range of cellular processes by silencing the gene expression at the protein and/or mRNA...
Hui Liu, Dong Yue, Yidong Chen, Shou-Jiang Gao, Yu...
ICMI
2003
Springer
131views Biometrics» more  ICMI 2003»
15 years 4 months ago
TorqueBAR: an ungrounded haptic feedback device
Kinesthetic feedback is a key mechanism by which people perceive object properties during their daily tasks – particularly inertial properties. For example, transporting a glass...
Colin Swindells, Alex Unden, Tao Sang
ICRA
2010
IEEE
145views Robotics» more  ICRA 2010»
14 years 10 months ago
Reinforcement learning of motor skills in high dimensions: A path integral approach
— Reinforcement learning (RL) is one of the most general approaches to learning control. Its applicability to complex motor systems, however, has been largely impossible so far d...
Evangelos Theodorou, Jonas Buchli, Stefan Schaal
80
Voted
GECCO
2007
Springer
138views Optimization» more  GECCO 2007»
15 years 5 months ago
Reducing the space-time complexity of the CMA-ES
A limited memory version of the covariance matrix adaptation evolution strategy (CMA-ES) is presented. This algorithm, L-CMA-ES, improves the space and time complexity of the CMA-...
James N. Knight, Monte Lunacek