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» Variational methods for Reinforcement Learning
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NIPS
1996
15 years 1 months ago
Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
Jeff G. Schneider
103
Voted
ML
1998
ACM
136views Machine Learning» more  ML 1998»
15 years 8 days ago
Co-Evolution in the Successful Learning of Backgammon Strategy
Following Tesauro’s work on TD-Gammon, we used a 4000 parameter feed-forward neural network to develop a competitive backgammon evaluation function. Play proceeds by a roll of t...
Jordan B. Pollack, Alan D. Blair
ACCV
2010
Springer
15 years 1 months ago
Abstraction and Generalization of 3D structure for recognition in large intra-class variation
Humans have abstract models for object classes which helps recognize previously unseen instances, despite large intra-class variations. Also objects are grouped into classes based...
Gowri Somanath, Chandra Kambhamettu
104
Voted
FBIT
2007
IEEE
15 years 7 months ago
Learning to Drive a Real Car in 20 Minutes
The paper describes our first experiments on Reinforcement Learning to steer a real robot car. The applied method, Neural Fitted Q Iteration (NFQ) is purely data-driven based on ...
Martin Riedmiller, Michael Montemerlo, Hendrik Dah...
94
Voted
ACL
2010
14 years 10 months ago
Reading between the Lines: Learning to Map High-Level Instructions to Commands
In this paper, we address the task of mapping high-level instructions to sequences of commands in an external environment. Processing these instructions is challenging--they posit...
S. R. K. Branavan, Luke S. Zettlemoyer, Regina Bar...