In this paper we extend the predicate logic introduced in [Beauquier et al. 2002] in order to deal with Semi-Markov Processes. We prove that with respect to qualitative probabilistic properties, model checking is decidable for this logic applied to SemiMarkov Processes. Furthermore we apply our logic to Probabilistic Timed Automata considering classical and urgent semantics, and considering als...

We provide two interpretations, over nondeterministic and probabilistic processes, of PML, the probabilistic version of HennessyMilner logic used by Larsen and Skou to characterize bisimilarity of probabilistic processes without internal nondeterminism. We also exhibit two new bisimulation-based equivalences, which are in full agreement with the two different interpretations of PML. The new equ...

The calculus of Mobile Ambients has been introduced for expressing mobility and mobile computation. In this paper we present a probabilistic version of Mobile Ambients by augmenting the syntax of the original Ambient Calculus with a (guarded) probabilistic choice operator. To allow for the representation of both the probabilistic behaviour introduced through the new probabilistic choice operato...

In this paper we extend the predicate logic introduced in [BRS02] in order to deal with Semi-Markov Processes. We prove that with respect to qualitative probabilistic properties, model checking is decidable for this logic applied to Semi-Markov Processes. Furthermore we apply our logic to Probabilistic Timed Automata considering classical and urgent semantics, and considering also predicates on...

We present a novel approach to probabilistic description logic programs for the Semantic Web in which disjunctive logic programs under the answer set semantics are tightly coupled with description logics and Bayesian probabilities. The approach has several nice features. In particular, it is a logic-based representation formalism that naturally fits into the landscape of semantic web languages....

This paper presents PFLP, a library for probabilistic programming in the functional logic programming language Curry. It demonstrates how the concepts of a functional logic programming language support the implementation of a library for probabilistic programming. In fact, the paradigms of functional logic and probabilistic programming are closely connected. That is, we can apply techniques fro...

This paper introduces a probabilistic description logic that adds probabilistic inclusions to the popular logic ALC, and derives inference algorithms for inference in the logic. The probabilistic logic, referred to as CRALC (“credal” ALC), combines the usual acyclicity condition with a Markov condition; in this context, inference is equated with calculation of (bounds on) posterior probability ...

In this paper we show the embedding of Hybrid Probabilistic Logic Programs into the rather general framework of Residuated Logic Programs, where the main results of (deenite) logic programming are validly extrapolated. The importance of this result is that for the rst time a framework encompassing several quite distinct logic programming more general semantical structure paving the way for deen...

We introduce probabilistic many-valued logic programs in which the implication connective is interpreted as material implication. We show that probabilistic many-valued logic programming is computationally more complex than classical logic programming. More precisely, some deduction problems that are P-complete for classical logic programs are shown to be co-NP-complete for probabilistic many-v...

Current literature offers a number of different approaches to what could generally be called “probabilistic logic programming”. These are usually based on Horn clauses. Here, we introduce a new formalism, Logic Programs with Annotated Disjunctions, based on disjunctive logic programs. In this formalism, each of the disjuncts in the head of a clause is annotated with a probability. Viewing such ...