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» Exponentiated Gradient Methods for Reinforcement Learning
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JMLR
2008
230views more  JMLR 2008»
13 years 6 months ago
Exponentiated Gradient Algorithms for Conditional Random Fields and Max-Margin Markov Networks
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
ESANN
2008
13 years 7 months ago
Similarities and differences between policy gradient methods and evolution strategies
Natural policy gradient methods and the covariance matrix adaptation evolution strategy, two variable metric methods proposed for solving reinforcement learning tasks, are contrast...
Verena Heidrich-Meisner, Christian Igel
IROS
2006
IEEE
113views Robotics» more  IROS 2006»
14 years 7 days ago
Policy Gradient Methods for Robotics
— The aquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-struc...
Jan Peters, Stefan Schaal
NIPS
2007
13 years 7 months ago
Incremental Natural Actor-Critic Algorithms
We present four new reinforcement learning algorithms based on actor-critic and natural-gradient ideas, and provide their convergence proofs. Actor-critic reinforcement learning m...
Shalabh Bhatnagar, Richard S. Sutton, Mohammad Gha...
ICANN
2005
Springer
13 years 11 months ago
Reinforcement Learning in MirrorBot
For this special session of EU projects in the area of NeuroIT, we will review the progress of the MirrorBot project with special emphasis on its relation to reinforcement learning...
Cornelius Weber, David Muse, Mark Elshaw, Stefan W...