We consider the problem of characterising expected hitting times and hitting probabilities for
imprecise Markov chains. To this end, we consider three distinct ways in which imprecise …

Standard techniques for model checking stochastic multi-agent systems usually assume the
transition probabilities describing the system dynamics to be stationary and completely …

We propose two sum-product laws for imprecise Markov chains, and use these laws to
derive two algorithms to efficiently compute lower and upper expectations for imprecise …

Stochastic multi-agent systems raise the necessity to extend probabilistic model checking to
the epistemic domain. Results in this direction have been achieved by epistemic extensions …

In recent years probabilistic model checking has become an important area of research
because of the diffusion of computational systems of stochastic nature. Despite its great …

This paper proposes a method for fitting a two-state imprecise Markov chain to time series
data from a two-state non-Markovian process. Such non-Markovian processes are common …

Contemporary society is increasingly dependent on the use of autonomous computational
systems. Being sure that these systems behave appropriately and do what they have been …