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ICTAI
2000
IEEE
15 years 10 months ago
Building efficient partial plans using Markov decision processes
Markov Decision Processes (MDP) have been widely used as a framework for planning under uncertainty. They allow to compute optimal sequences of actions in order to achieve a given...
Pierre Laroche
AIPS
2008
15 years 9 months ago
Bounded-Parameter Partially Observable Markov Decision Processes
The POMDP is considered as a powerful model for planning under uncertainty. However, it is usually impractical to employ a POMDP with exact parameters to model precisely the real-...
Yaodong Ni, Zhi-Qiang Liu
FLAIRS
2007
15 years 9 months ago
Probabilistic Knowledge Processing and Remaining Uncertainty
Information is indispensable in preparing economic decisions purposefully. In this paper knowledge is represented by a probability distribution. Knowledge acquisition is realized ...
Elmar Reucher, Friedhelm Kulmann
FLAIRS
2008
15 years 9 months ago
A Novel Prioritization Technique for Solving Markov Decision Processes
We address the problem of computing an optimal value function for Markov decision processes. Since finding this function quickly and accurately requires substantial computation ef...
Jilles Steeve Dibangoye, Brahim Chaib-draa, Abdel-...
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AUSAI
2006
Springer
15 years 8 months ago
An Efficient Alternative to SVM Based Recursive Feature Elimination with Applications in Natural Language Processing and Bioinfo
The SVM based Recursive Feature Elimination (RFE-SVM) algorithm is a popular technique for feature selection, used in natural language processing and bioinformatics. Recently it wa...
Justin Bedo, Conrad Sanderson, Adam Kowalczyk