A process is called stochastic when its time-evolution is to some
extent uncertain. To model and reason with such uncertainty, we
use methods from probability theory. This allows us to analyse the
behaviour of these processes, and to design or influence them in
order to make their behaviour optimal or desirable.
One crucial problem is that most often we are not only uncertain
about the processes themselves, but also about the validity of the
probabilistic models we use for studying them. The theory of
imprecise probability is a recent development of probability theory
that is designed to dealing with this so-called model uncertainty in
a robust way.
The project aims first of all at further developing this general
theory, all the while concentrating on techniques that are useful
for, and tailored towards, working with stochastic processes. At
the same time, we will apply and evaluate the developed methods
and techniques in the practically important area of queueing
applications for communication systems.
The project brings together two research groups at Ghent University:
SYSTeMS, whose expertise lies in robust uncertainty modelling
using imprecise probabilities, and SMACS, who are focused
on queueing theory and applications in communication.