We propose a generic categorical framework for learning unknown formal languages of
various types (eg finite or infinite words, weighted and nominal languages). Our approach is …

State-based models of concurrent systems are traditionally considered under a variety of
notions of process equivalence. In the particular case of labelled transition systems, these …

Partition refinement is a method for minimizing automata and transition systems of various
types. Recently, we have developed a partition refinement algorithm that is generic in the …

Coalgebraic bisimilarity minimization generalizes classical automaton minimization to a
large class of automata whose transition structure is specified by a functor, subsuming …

We study the synthesis problem for systems with a parameterized number of processes. As
in the classical case due to Church, the system selects actions depending on the program …

There are different categorical approaches to variations of transition systems and their
bisimulations. One is coalgebra for a functor G, where a bisimulation is defined as a span of …

Positive data languages are languages over an infinite alphabet closed under possibly non-
injective renamings of data values. Informally, they model properties of data words …

Partition refinement is a method for minimizing automata and transition systems of various
types. Recently, we have developed a partition refinement algorithm that is generic in the …

Coalgebras for an endofunctor provide a category-theoretic framework for modeling a wide
range of state-based systems of various types. We provide an iterative construction of the …

We are motivated by the following question: which nominal languages admit an active
learning algorithm? This question was left open in previous work, and is particularly …