Accurate description of program inputs remains a critical challenge in the field of
programming languages. Active learning, as a well-established field, achieves exact …

Ensuring the correctness and reliability of deep neural networks is a challenge. Suitable
formal analysis and verification techniques have yet to be developed. One promising …

This paper presents (i) an active learning algorithm for visibly pushdown grammars and (ii)
shows its applicability for learning surrogate models of recurrent neural networks (RNNs) …

Automata learning is a technique that has successfully been applied in verification, with the
automaton type varying depending on the application domain. Adaptations of automata …

We study the problem of learning regular tree languages from text. We show that the
framework of function distinguishability as introduced in our ALT 2000 paper is …

Learning Pomset Automata. Page 524 Learning Pomset Automata ⋆ Gerco van Heerdt1(),
Tobias Kappé2, Jurriaan Rot3, and Alexandra Silva1 1 University College London, London, UK …

The problem of identifying a probabilistic context free grammar has two aspects: the first is
determining the grammar's topology (the rules of the grammar) and the second is estimating …

We study a categorical generalisation of tree automata, as $\Sigma $-algebras for a fixed
endofunctor $\Sigma $ endowed with initial and final states. Under mild assumptions about …

We devise a learning algorithm for deterministically recognizable tree series where the
weights are taken from a commutative group. For this, we use an adaptation of the minimal …

We present two active learning algorithms for sound deterministic negotiations. Sound
deterministic negotiations are models of distributed systems, a kind of Petri nets or Zielonka …