119 citations · 168 across the 14 of their papers we have counts for
15 papers
Automata Learning versus Process Mining: The Case for User Journeys
Paul Kobialka, Andrea Pferscher, Bernhard K. Aichernig +2
With the servitization of business, understanding how users experience services becomes a crucial success factor for companies. Therefore, there is a need to include feedback from…
Extending AALpy with Passive Learning: A Generalized State-Merging Approach
Benjamin von Berg, Bernhard K. Aichernig
AALpy is a well-established open-source automata learning library written in Python with a focus on active learning of systems with IO behavior. It provides a wide range of state-o…
Learning Environment Models with Continuous Stochastic Dynamics
Martin Tappler, Edi Muškardin, Bernhard K. Aichernig +1
Solving control tasks in complex environments automatically through learning offers great potential. While contemporary techniques from deep reinforcement learning (DRL) provide ef…
On the Relationship Between RNN Hidden State Vectors and Semantic Ground Truth
Edi Muškardin, Martin Tappler, Ingo Pill +2
We examine the assumption that the hidden-state vectors of recurrent neural networks (RNNs) tend to form clusters of semantically similar vectors, which we dub the clustering hypot…
Fingerprinting and Analysis of Bluetooth Devices with Automata Learning
Andrea Pferscher, Bernhard K. Aichernig
Automata learning is a technique to automatically infer behavioral models of black-box systems. Today's learning algorithms enable the deduction of models that describe complex sys…
Active vs. Passive: A Comparison of Automata Learning Paradigms for Network Protocols
Bernhard K. Aichernig, Edi Muškardin, Andrea Pferscher
Active automata learning became a popular tool for the behavioral analysis of communication protocols. The main advantage is that no manual modeling effort is required since a beha…