In this paper, we revisit the active learning of timed languages recognizable by event-
recording automata. Our framework employs a method known as greybox learning, which …

We present an algorithm for active learning of deterministic timed automata with multiple
clocks. The algorithm is within the querying framework of Angluin's L* algorithm and follows …

We present the first algorithm for query learning of a general class of Mealy machines with
timers (MMTs) in a black-box context. Our algorithm is an extension of the L# algorithm of …

Active learning of finite automata has been vigorously pursued for the purposes of analysis
and explanation of black-box systems. In this paper, we study an L*-style learning algorithm …

The well-known Nerode equivalence for finite words plays a fundamental role in our
understanding of the class of regular languages. The equivalence leads to the Myhill …

Active automata learning (AAL) can infer accurate automata models of real-time systems
(RTS). However, even efficient AAL methods for RTS, like learning Mealy machines with …

Computer systems are ubiquitous nowadays and it goes without saying that their
correctness is of capital importance in a lot of cases. However, identifying bugs and faults in …

We introduce an algorithmic framework to decide the language inclusion for languages of
infinite words. We define algorithms for different decidable cases like the inclusion between …

Most hybrid system identification methods rely on passive learning techniques, limiting the
accuracy of the learned model to the data at hand. We present an active learning approach …