An Efficient Algorithm for Learning Event-Recording Automata

  • Shang-Wei Lin
  • Étienne André
  • Jin Song Dong
  • Jun Sun
  • Yang Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6996)

Abstract

In inference of untimed regular languages, given an unknown language to be inferred, an automaton is constructed to accept the unknown language from answers to a set of membership queries each of which asks whether a string is contained in the unknown language. One of the most well-known regular inference algorithms is the L* algorithm, proposed by Angluin in 1987, which can learn a minimal deterministic finite automaton (DFA) to accept the unknown language. In this work, we propose an efficient polynomial time learning algorithm, TL*, for timed regular language accepted by event-recording automata. Given an unknown timed regular language, TL* first learns a DFA accepting the untimed version of the timed language, and then passively refines the DFA by adding time constraints. We prove the correctness, termination, and minimality of the proposed TL* algorithm.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Shang-Wei Lin
    • 1
  • Étienne André
    • 1
  • Jin Song Dong
    • 1
  • Jun Sun
    • 2
  • Yang Liu
    • 1
  1. 1.School of ComputingNational University of SingaporeSingapore
  2. 2.Singapore University of Technology and DesignSingapore

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