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» Approximate predictive state representations
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JAIR
2010
145views more  JAIR 2010»
13 years 6 months ago
Planning with Noisy Probabilistic Relational Rules
Noisy probabilistic relational rules are a promising world model representation for several reasons. They are compact and generalize over world instantiations. They are usually in...
Tobias Lang, Marc Toussaint
ICML
2009
IEEE
14 years 8 months ago
Approximate inference for planning in stochastic relational worlds
Relational world models that can be learned from experience in stochastic domains have received significant attention recently. However, efficient planning using these models rema...
Tobias Lang, Marc Toussaint
ICAI
2009
13 years 5 months ago
On the Construction of Initial Basis Function for Efficient Value Function Approximation
- We address the issues of improving the feature generation methods for the value-function approximation and the state space approximation. We focus the improvement of feature gene...
Chung-Cheng Chiu, Kuan-Ta Chen

Publication
222views
14 years 4 months ago
Algorithms and Bounds for Rollout Sampling Approximate Policy Iteration
Abstract: Several approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a supervis...
Christos Dimitrakakis, Michail G. Lagoudakis
PAMI
2010
248views more  PAMI 2010»
13 years 6 months ago
Coupled Prediction Classification for Robust Visual Tracking
—This paper addresses the problem of robust template tracking in image sequences. Our work falls within the discriminative framework in which the observations at each frame yield...
Ioannis Patras, Edwin R. Hancock