Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
The work in this paper is directed towards sophisticated formalisms for reasoning under probabilistic uncertainty in ontologies in the Semantic Web. Ontologies play a central role...
We review a method of generating logical rules, or axioms, from empirical data. This method, using closed set properties of formal concept analysis, has been previously described ...
This paper defines a probabilistic barbed congruence which turns out to coincide with observational equivalence in a probabilistic extension of CCS. Based on this coincidence resu...
— This paper addresses the computational overhead involved in probabilistic reachability computations for a general class of controlled stochastic hybrid systems. An approximate ...
Alessandro Abate, Maria Prandini, John Lygeros, Sh...