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PAC Learning of Deterministic One-Clock Timed Automata

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Formal Methods and Software Engineering (ICFEM 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12531))

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Abstract

We study the problem of learning deterministic one-clock timed automata in the framework of PAC (probably approximately correct) learning. The use of PAC learning relaxes the assumption of having a teacher that can answer equivalence queries exactly, replacing it with approximate answers from testing on a set of samples. The framework provides correctness guarantees in terms of error and confidence parameters. We further discuss several improvements to the basic PAC algorithm. This includes a special sampling method, and the use of comparator and counterexample minimization to reduce the number of equivalence queries. We implemented a prototype for our learning algorithm, and conducted experiments on learning the TCP protocol as well as a number of randomly generated automata. The results demonstrate the effectiveness of our approach, as well as the importance of the various improvements for learning complex models.

This work has been partially funded by NSFC under grant No. 61972284, No. 61625206, No. 61732001 and No. 61836005, and by the CAS Pioneer Hundred Talents Program under grant No. Y9RC585036.

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Author information

Authors and Affiliations

  1. School of Software Engineering, Tongji University, Shanghai, China

    Wei Shen, Jie An & Miaomiao Zhang

  2. State Key Laboratory of Computer Science, Institute of Software, CAS, Beijing, China

    Bohua Zhan, Bai Xue & Naijun Zhan

  3. University of Chinese Academy of Sciences, Beijing, China

    Bohua Zhan, Bai Xue & Naijun Zhan

Authors
  1. Wei Shen
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  2. Jie An
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  3. Bohua Zhan
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  4. Miaomiao Zhang
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  5. Bai Xue
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  6. Naijun Zhan
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Corresponding authors

Correspondence to Bohua Zhan , Miaomiao Zhang or Naijun Zhan .

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Editors and Affiliations

  1. Nanyang Technological University, Singapore, Singapore

    Shang-Wei Lin

  2. School of Information and Communication Technology, Griffith University, Nathan Campus, QLD, Australia

    Zhe Hou

  3. Defence Science and Technology Group, Denver, CO, USA

    Brendan Mahony

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Shen, W., An, J., Zhan, B., Zhang, M., Xue, B., Zhan, N. (2020). PAC Learning of Deterministic One-Clock Timed Automata. In: Lin, SW., Hou, Z., Mahony, B. (eds) Formal Methods and Software Engineering. ICFEM 2020. Lecture Notes in Computer Science(), vol 12531. Springer, Cham. https://doi.org/10.1007/978-3-030-63406-3_8

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  • DOI: https://doi.org/10.1007/978-3-030-63406-3_8

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  • Online ISBN: 978-3-030-63406-3

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