• Alexis Linard
  • R Smetsers
  • FW Vaandrager
  • Umar Waqas
  • Joost van Pinxten
  • Sicco Verwer
A classical problem in grammatical inference is to identify a deterministic finite automaton (DFA) from a set of positive and negative examples. In this paper, we address the related – yet seemingly novel – problem of identifying a set of DFAs from examples that belong to different unknown sim ple regular languages. We propose two methods based on compression for
clustering the observed positive examples. We apply our methods to a set of print jobs submitted to large industrial printers.
Original languageEnglish
Title of host publicationArXiv Preprint
Number of pages4
Publication statusPublished - 6 Jun 2017

ID: 28357189