- Heike Clemens (for administrative matters)
We aim at combining automata learning with the generic framework of coalgebra. In recent years, automata learning was shown to be a useful tool in the verification of software components and in the discovery of implementation mistakes in black-box systems. This inspired many generalized learning algorithms in the categorical language of universal coalgebra, making it possible to apply the methods to other system types (e.g. nominal automata). The meeting serves as a platform for exchanging and combining the most recent research results of the two fields.