Types of Trusted Information That Make DFA Identification with Correction Queries Feasible

  • Cristina Tîrnăucă
  • Cătălin Ionuţ Tîrnăucă
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6482)


In the query learning model, the problem of efficiently identifying a deterministic finite automaton (DFA) has been widely investigated. While DFAs are known to be polynomial time learnable with a combination of membership queries (MQs) and equivalence queries (EQs), each of these types of queries alone are not enough to provide sufficient information for the learner. Therefore, the possibility of having some extra-information shared between the learner and the teacher has been discussed. In this paper, the problem of efficient DFA identification with correction queries (CQs) - an extension of MQs - when additional information is provided to the learner is addressed. We show that knowing the number of states of the target DFA does not help (similar to the case of MQs or EQs), but other parameters such as the reversibility or injectivity degree are useful.


deterministic finite automaton correction query injectivity degree 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Cristina Tîrnăucă
    • 1
  • Cătălin Ionuţ Tîrnăucă
    • 2
  1. 1.Departamento de Matemáticas, Estadística y ComputaciónUniversidad de CantabriaSantanderSpain
  2. 2.Research Group on Mathematical LinguisticsUniversitat Rovira i VirgiliTarragonaSpain

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