(eng): The presented contribution deals with formal logical models capturing both vagueness and uncertainty. The vagueness facet of such models is represented by fuzzy events (many-valued events) which are measured by degrees of uncertainty (belief). Therefore, any logic for fuzzy events under uncertainty must have a sufficient expressive power to model inference on the side of the fuzzy events as well as to reproduce reasoning with degrees of uncertainty associated with those events. In particular, the logic chosen should be versatile enough to include in its language virtually any of the approaches to uncertainty processing, such as probability theory, possibility/necessity, Dempster-Shafer theory etc. The meaning of fuzzy events and their associated uncertainty degrees is usually rendered through de Finetti coherence criterion.