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ECAI
1990
Springer
15 years 6 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
15 years 6 months 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
15 years 5 months 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»
15 years 2 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»
15 years 2 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