Efficient learning of real time one-counter automata

  • Amr F. Fahmy
  • Robert S. Roos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 997)


We present an efficient learning algorithm for languages accepted by deterministic real time one-counter automata (ROCA). The learning algorithm works by first learning an initial segment, B n , of the infinite state machine that accepts the unknown language and then decomposing it into a complete control structure and a partial counter. A new, efficient ROCA decomposition algorithm, which will be presented in detail, allows this result. The decomposition algorithm works in time O(n2log(n)) where nc is the number of states of B n for some language-dependent constant c. If Angluin's algorithm for learning regular languages is used to learn B n and the complexity of this step is h(n, m), where m is the length of the longest counterexample necessary for Angluin's algorithm, the complexity of our algorithm is O(h(n,m) + n2log(n)).


State Machine Finite State Machine Regular Language Exit Point Input String 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Amr F. Fahmy
    • 1
  • Robert S. Roos
    • 2
  1. 1.Aiken Computation LabHarvard UniversityCambridgeUSA
  2. 2.Department of Computer ScienceSmith CollegeNorthamptonUSA

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