Combinatorial optimisation problems often contain uncertainty that has to be taken into account to produce realistic solutions. However, existing modelling systems either do not support uncertainty, or do not support combinatorial features, such as integer variables and non-linear constraints. This paper presents an extension of the MINIZINC modelling language that supports uncertainty. Stochas...

The modelling of organic pollutants in the environment is burdened by numerous uncertainties. Not only parameter values are uncertain but often also the mass and timing of pesticide application. By introducing transformation products (TPs) into modelling, further uncertainty, coming from the dependence of these substances on their parent compounds and the introduction of new model parameters, i...

An essential requirement for a comprehensive use of hybrid data is the consideration and processing of its uncertainty. Erroneous interpretations of analyses can be avoided if uncertainty is integrated as a mandatory component, stored and considered in all operations. In this contribution, a probabilistic approach is presented for modelling geometric and thematic uncertainty. By means of a floo...

In applications there occur different forms of uncertainty. The twomost important types are randomness (stochastic variability) and imprecision(fuzziness). In modelling, the dominating concept to describe uncertainty isusing stochastic models which are based on probability. However, fuzzinessis not stochastic in nature and therefore it is not considered in probabilisticmodels.Since many years t...

Automata are simple mathematical objects with unexpected computational, mathematical, modelling and explanatory capabilities. This paper examines some relations between automata and physics. Automata will be used to model quantum uncertainty and quantum computation. Finally, mathematical proofs will be discussed from the perspective of quantum automata. 1 Modelling Quantum Uncertainty with Auto...

Formal modelling languages such as process algebras are widespread and effective tools in computational modelling. However, handling data and uncertainty in a statistically meaningful way is an open problem in formal modelling, severely hampering the usefulness of these elegant tools in many real world applications. Here we introduce ProPPA, a process algebra which incorporates uncertainty in t...