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» An MDP Approach for Explanation Generation
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FLAIRS
2007
13 years 10 months ago
Explaining Task Processing in Cognitive Assistants that Learn
As personal assistant software matures and assumes more autonomous control of its users’ activities, it becomes more critical that this software can explain its task processing....
Deborah L. McGuinness, Alyssa Glass, Michael Wolve...
AI
2006
Springer
13 years 7 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
CSB
2005
IEEE
129views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Rule Clustering and Super-rule Generation for Transmembrane Segments Prediction
The explanation of a decision is important for the acceptance of machine learning technology in bioinformatics applications such as protein structure prediction. In past research,...
Jieyue He, Bernard Chen, Hae-Jin Hu, Robert W. Har...
WINET
2010
127views more  WINET 2010»
13 years 5 months ago
A Markov Decision Process based flow assignment framework for heterogeneous network access
We consider a scenario where devices with multiple networking capabilities access networks with heterogeneous characteristics. In such a setting, we address the problem of effici...
Jatinder Pal Singh, Tansu Alpcan, Piyush Agrawal, ...
SAS
2004
Springer
103views Formal Methods» more  SAS 2004»
14 years 27 days ago
Information Flow Analysis in Logical Form
Abstract. We specify an information flow analysis for a simple imperative language, using a Hoare-like logic. The logic facilitates static checking of a larger class of programs t...
Torben Amtoft, Anindya Banerjee