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ICML
2009
IEEE
14 years 11 months ago
Learning nonlinear dynamic models
We present a novel approach for learning nonlinear dynamic models, which leads to a new set of tools capable of solving problems that are otherwise difficult. We provide theory sh...
John Langford, Ruslan Salakhutdinov, Tong Zhang
ICML
2002
IEEE
14 years 11 months ago
Discovering Hierarchy in Reinforcement Learning with HEXQ
An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts to decompose and solve a model-free factored MDP h...
Bernhard Hengst
ECML
2006
Springer
14 years 17 hour ago
Reinforcement Learning for MDPs with Constraints
In this article, I will consider Markov Decision Processes with two criteria, each defined as the expected value of an infinite horizon cumulative return. The second criterion is e...
Peter Geibel
COLING
2008
13 years 11 months ago
Scaling up Analogical Learning
Recent years have witnessed a growing interest in analogical learning for NLP applications. If the principle of analogical learning is quite simple, it does involve complex steps ...
Philippe Langlais, François Yvon
ICRA
1995
IEEE
151views Robotics» more  ICRA 1995»
14 years 1 months ago
Learning Impedance Control for Robotic Manipulators
—Learning control is a concept for controlling dynamic systems in an iterative manner. It arises from the recognition that robotic manipulators are usually used to perform repeti...
Chien-Chern Cheah, Danwei Wang