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» Metacognitive Control and Optimal Learning
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ICMLA
2010
14 years 7 months ago
Multi-Agent Inverse Reinforcement Learning
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...
Sriraam Natarajan, Gautam Kunapuli, Kshitij Judah,...
AMS
2005
Springer
112views Robotics» more  AMS 2005»
15 years 3 months ago
Combining Learning and Programming for High-Performance Robot Controllers
Abstract. The implementation of high-performance robot controllers for complex control tasks such as playing autonomous robot soccer is tedious, errorprone, and a never ending prog...
Alexandra Kirsch, Michael Beetz
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
13 years 12 hour ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
IJCNN
2007
IEEE
15 years 3 months ago
Encoding Complete Body Models Enables Task Dependent Optimal Behavior
— Many neural network models of (human) motor learning focus on the acquisition of direct goal-to-action mappings, which results in rather inflexible motor control programs. We ...
Oliver Herbort, Martin V. Butz
KI
2009
Springer
15 years 4 months ago
Machine Learning Techniques for Selforganizing Combustion Control
Abstract. This paper presents the overall system of a learning, selforganizing, and adaptive controller used to optimize the combustion process in a hard-coal fired power plant. T...
Erik Schaffernicht, Volker Stephan, Klaus Debes, H...