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» Learning operational requirements from goal models
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ML
2002
ACM
100views Machine Learning» more  ML 2002»
13 years 7 months ago
Structure in the Space of Value Functions
Solving in an efficient manner many different optimal control tasks within the same underlying environment requires decomposing the environment into its computationally elemental ...
David J. Foster, Peter Dayan
ICCV
2007
IEEE
14 years 9 months ago
Learning Structured Appearance Models from Captioned Images of Cluttered Scenes
Given an unstructured collection of captioned images of cluttered scenes featuring a variety of objects, our goal is to learn both the names and appearances of the objects. Only a...
Michael Jamieson, Afsaneh Fazly, Sven J. Dickinson...
APCHI
1998
IEEE
14 years 1 days ago
Knowledge Required for Understanding Task-Oriented Instructions
When they encounter problems with a novel or infrequently performed task, experienced users often complete their work by referring to manuals and trying task-oriented exploration....
Muneo Kitajima, Peter G. Polson
TSMC
2008
177views more  TSMC 2008»
13 years 6 months ago
Adaptive Critic Learning Techniques for Engine Torque and Air-Fuel Ratio Control
A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning con...
Derong Liu, Hossein Javaherian, Olesia Kovalenko, ...
IJRR
2008
139views more  IJRR 2008»
13 years 7 months ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal