As scientists, we have always tried to understand the things we see around us. We observe phenomena in nature, and then use these observations to construct a model, preferably based on a theory. The aim of such a model is to help us in our understanding of the dynamics of nature and to make more or less successful predictions. But what exactly constitutes a good model?

If our model is such that future states only depend on the present, we speak of determinism. In that case one would expect perfect predictability of the model. However nonlinear deterministic systems usually exhibit chaos, which means that longer term predictions become uncertain. The field which studies the time evolution of deterministic systems is known as dynamical systems, and can offer us insights into the measure of uncertainty in the predictions.

In practice, we are not always able to model a system deterministically, and we need to take randomness into account: this leads to a stochastic model. How does this randomness influence the certainty of our model? How can we apply our knowledge of probability and statistics to account for this? And what are the consequences for society if these uncertainties are interpreted wrong?

All these questions and more will be addressed at the FMF-symposium on November 29th 2011 at ForumImages. The target audience are students of Mathematics, Physics, Astrophysics and Computer Science but the symposium is open to all those who are interested.