Relatively complete verification of probabilistic programs: an expressive language for expectation-based reasoning

Language-Based Program Verification via Expressive Types

Experimentation of an expectation maximization algorithm for probabilistic logic programs

Statistical Relational Learning and Probabilistic Inductive Logic Programming are two emerging fields that use representation languages able to combine logic and probability. In the field of Logic Programming, the distribution semantics is one of the prominent approaches for representing uncertainty and underlies many languages such as ICL, PRISM, ProbLog and LPADs. Learning the parameters for ...

CSLLHA: an Expressive Language for Statistical Verification of Stochastic Models

We introduce a new temporal logic formalism, named CSLLHA, for the verification of discrete event stochastic processes (DESP). Being inspired by existing stochastic logic, such as, the Continuous Stochastic Logic (CSL) and its following action-state (asCSL) and timed automata (CSLTA) evolutions, CSLLHA extends them in two respects: firstly it targets a much broader class of stochastic models (i...

HASL: an expressive language for statistical verification of stochastic models

We introduce the Hybrid Automata Stochastic Logic (HASL), a new temporal logic formalism for the verification of discrete event stochastic processes (DESP). HASL employs Linear Hybrid Automata (LHA) as machineries to select prefixes of relevant execution paths of a DESP D. The advantage with LHA is that rather elaborate information can be collected on-the-fly during path selection, providing th...

Verification of Probabilistic Programs

A general method for proving properties of probabilistic programs is presented, This method generalizes the intermediate assertion method in that it extends a given assertion on the output distribution into an invariant assertion on all intermediate distributions, too. The proof method is shown to be sound and complete for programs which terminate with probability 1. A dual approach, based on t...