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ECAI
1990
Springer
14 years 1 months ago
Probabilistic Belief Logics
Modal logics based on Kripke style semantics are the prominent formalismin AI for modeling beliefs. Kripke semantics involve a collection of possible worlds and a relation among t...
Fahiem Bacchus
FSTTCS
2006
Springer
14 years 21 days ago
Testing Probabilistic Equivalence Through Reinforcement Learning
We propose a new approach to verification of probabilistic processes for which the model may not be available. We use a technique from Reinforcement Learning to approximate how far...
Josee Desharnais, François Laviolette, Sami...
ICLP
2010
Springer
14 years 14 days ago
Improving the Efficiency of Gibbs Sampling for Probabilistic Logical Models by Means of Program Specialization
Abstract. There is currently a large interest in probabilistic logical models. A popular algorithm for approximate probabilistic inference with such models is Gibbs sampling. From ...
Daan Fierens
CORR
2008
Springer
107views Education» more  CORR 2008»
13 years 9 months ago
Metric Structures and Probabilistic Computation
Abstract. Continuous first-order logic is used to apply model-theoretic analysis to analytic structures (e.g. Hilbert spaces, Banach spaces, probability spaces, etc.). Classical co...
Wesley Calvert
CORR
2008
Springer
75views Education» more  CORR 2008»
13 years 9 months ago
A new probabilistic transformation of belief mass assignment
In this paper, we propose in Dezert-Smarandache Theory (DSmT) framework, a new probabilistic transformation, called DSmP, in order to build a subjective probability measure from an...
Jean Dezert, Florentin Smarandache