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» Approximate Learning of Dynamic Models
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146
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AIPS
2010
15 years 7 months ago
When Policies Can Be Trusted: Analyzing a Criteria to Identify Optimal Policies in MDPs with Unknown Model Parameters
Computing a good policy in stochastic uncertain environments with unknown dynamics and reward model parameters is a challenging task. In a number of domains, ranging from space ro...
Emma Brunskill
IUI
2012
ACM
14 years 17 days ago
Probabilistic pointing target prediction via inverse optimal control
Numerous interaction techniques have been developed that make “virtual” pointing at targets in graphical user interfaces easier than analogous physical pointing tasks by invok...
Brian D. Ziebart, Anind K. Dey, J. Andrew Bagnell
ATAL
2008
Springer
15 years 7 months ago
On the usefulness of opponent modeling: the Kuhn Poker case study
The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
Alessandro Lazaric, Mario Quaresimale, Marcello Re...
142
Voted
JCDL
2010
ACM
184views Education» more  JCDL 2010»
15 years 10 months ago
Evaluating topic models for digital libraries
Topic models could have a huge impact on improving the ways users find and discover content in digital libraries and search interfaces, through their ability to automatically lea...
David Newman, Youn Noh, Edmund M. Talley, Sarvnaz ...
SCA
2007
15 years 7 months ago
Legendre fluids: a unified framework for analytic reduced space modeling and rendering of participating media
In this paper, we present a unified framework for reduced space modeling and rendering of dynamic and nonhomogenous participating media, like snow, smoke, dust and fog. The key id...
Mohit Gupta, Srinivasa G. Narasimhan