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» Learning Options for an MDP from Demonstrations
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ICRA
2010
IEEE
143views Robotics» more  ICRA 2010»
13 years 3 months ago
Apprenticeship learning via soft local homomorphisms
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
Abdeslam Boularias, Brahim Chaib-draa
KCAP
2009
ACM
13 years 11 months ago
Interactively shaping agents via human reinforcement: the TAMER framework
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
W. Bradley Knox, Peter Stone

Publication
154views
12 years 7 months ago
Preference elicitation and inverse reinforcement learning
We state the problem of inverse reinforcement learning in terms of preference elicitation, resulting in a principled (Bayesian) statistical formulation. This generalises previous w...
Constantin Rothkopf, Christos Dimitrakakis
BIBE
2005
IEEE
13 years 10 months ago
Using Data Mining Techniques to Learn Layouts of Flat-File Biological Datasets
One of the major problems in biological data integration is that many data sources are stored as flat-files, with a variety of different layouts. Integrating data from such sour...
Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agra...
IUI
1997
ACM
13 years 9 months ago
Inductive Task Modeling for User Interface Customization
This paper describes ActionStreams, a system for inducing task models from observations of user activity. The model can represent several task structures: hierarchy, variable sequ...
David Maulsby