Learning Mealy Machines with One Timer

Frits Vaandrager, Roderick Bloem, Masoud Ebrahimi*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


We present Mealy machines with a single timer (MM1Ts), a class of models that is both sufficiently expressive to describe the real-time behavior of many realistic applications, and can be learned efficiently. We show how learning algorithms for MM1Ts can be obtained via a reduction to the problem of learning Mealy machines. We describe an implementation of an MM1T learner on top of LearnLib, and compare its performance with recent algorithms proposed by Aichernig et al. and An et al. on several realistic benchmarks.
Original languageEnglish
Title of host publicationLanguage and Automata Theory and Applications - 15th International Conference, LATA 2021, Proceedings
EditorsAlberto Leporati, Carlos Martín-Vide, Dana Shapira, Claudio Zandron
Place of PublicationCham
PublisherSpringer Nature Switzerland AG
Number of pages14
ISBN (Print)9783030681944
Publication statusPublished - 2021
Event14th-15th International Conference on Language and Automata Theory and Applications: LATA 2020&2021 - Mailand, Italy
Duration: 20 Sept 202124 Sept 2021

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th-15th International Conference on Language and Automata Theory and Applications


  • Automata learning
  • Mealy Machines
  • Timed automata
  • WiFi
  • WPA2

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Learning Mealy Machines with One Timer'. Together they form a unique fingerprint.

Cite this