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» Feature-Discovering Approximate Value Iteration Methods
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AAAI
2006
13 years 9 months ago
An Edge Deletion Semantics for Belief Propagation and its Practical Impact on Approximation Quality
We show in this paper that the influential algorithm of iterative belief propagation can be understood in terms of exact inference on a polytree, which results from deleting enoug...
Arthur Choi, Adnan Darwiche
NA
2007
120views more  NA 2007»
13 years 7 months ago
On choosing "optimal" shape parameters for RBF approximation
Many radial basis function (RBF) methods contain a free shape parameter that plays an important role for the accuracy of the method. In most papers the authors end up choosing this...
Gregory E. Fasshauer, Jack G. Zhang
JAIR
2006
160views more  JAIR 2006»
13 years 7 months ago
Anytime Point-Based Approximations for Large POMDPs
The Partially Observable Markov Decision Process has long been recognized as a rich framework for real-world planning and control problems, especially in robotics. However exact s...
Joelle Pineau, Geoffrey J. Gordon, Sebastian Thrun
GECCO
2004
Springer
14 years 1 months ago
Validating a Model of Colon Colouration Using an Evolution Strategy with Adaptive Approximations
The colour of colon tissue, which depends on the tissue structure, its optical properties, and the quantities of the pigments present in it, can be predicted by a physics-based mod...
Dzena Hidovic, Jonathan E. Rowe
AI
2006
Springer
13 years 11 months ago
Belief Selection in Point-Based Planning Algorithms for POMDPs
Abstract. Current point-based planning algorithms for solving partially observable Markov decision processes (POMDPs) have demonstrated that a good approximation of the value funct...
Masoumeh T. Izadi, Doina Precup, Danielle Azar