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» Variational methods for Reinforcement Learning
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ICML
2003
IEEE
14 years 8 months ago
Relativized Options: Choosing the Right Transformation
Relativized options combine model minimization methods and a hierarchical reinforcement learning framework to derive compact reduced representations of a related family of tasks. ...
Balaraman Ravindran, Andrew G. Barto
PRICAI
2000
Springer
13 years 11 months ago
Constructing an Autonomous Agent with an Interdependent Heuristics
When we construct an agent by integrating modules, there appear troubles concerning the autonomy of the agent if we introduce a heuristics that dominates the whole agent. Thus, we ...
Koichi Moriyama, Masayuki Numao
AAAI
2010
13 years 9 months ago
Relative Entropy Policy Search
Policy search is a successful approach to reinforcement learning. However, policy improvements often result in the loss of information. Hence, it has been marred by premature conv...
Jan Peters, Katharina Mülling, Yasemin Altun
EMNLP
2010
13 years 5 months ago
Turbo Parsers: Dependency Parsing by Approximate Variational Inference
We present a unified view of two state-of-theart non-projective dependency parsers, both approximate: the loopy belief propagation parser of Smith and Eisner (2008) and the relaxe...
André F. T. Martins, Noah A. Smith, Eric P....
CEC
2008
IEEE
13 years 9 months ago
Learning defect classifiers for visual inspection images by neuro-evolution using weakly labelled training data
This article presents results from experiments where a detector for defects in visual inspection images was learned from scratch by EANT2, a method for evolutionary reinforcement l...
Nils T. Siebel, Gerald Sommer