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SEMWEB
2010
Springer
15 years 4 months ago
Combining Approximation and Relaxation in Semantic Web Path Queries
We develop query relaxation techniques for regular path queries and combine them with query approximation in order to support flexible querying of RDF data when the user lacks know...
Alexandra Poulovassilis, Peter T. Wood
ICAI
2009
15 years 4 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
JAIR
2011
187views more  JAIR 2011»
15 years 1 months ago
A Monte-Carlo AIXI Approximation
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...
CVPR
2004
IEEE
16 years 8 months ago
Incremental Density Approximation and Kernel-Based Bayesian Filtering for Object Tracking
Statistical density estimation techniques are used in many computer vision applications such as object tracking, background subtraction, motion estimation and segmentation. The pa...
Bohyung Han, Dorin Comaniciu, Ying Zhu, Larry S. D...
PKDD
2009
Springer
152views Data Mining» more  PKDD 2009»
16 years 22 days ago
Feature Selection for Value Function Approximation Using Bayesian Model Selection
Abstract. Feature selection in reinforcement learning (RL), i.e. choosing basis functions such that useful approximations of the unkown value function can be obtained, is one of th...
Tobias Jung, Peter Stone