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Optimized Smart Sampling

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Bridging the Gap Between AI and Reality (AISoLA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14380))

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Abstract

We revisit the principle of Smart Sampling which makes it possible to apply Statistical Model Checking on stochastic and non-deterministic systems. We point out difficulties in the design of the initial algorithm and we propose effective solutions to solve them. Our contributions are implemented in the Plasma tool.

M. Parmentier is funded by a FNRS PhD Grant and A. Legay by a FNRS PDR - T013721.

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Notes

  1. 1.

    See https://www.prismmodelchecker.org/download.php for a description.

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Authors and Affiliations

  1. ICTEAM, UCLouvain, 1341, Louvain-la-Neuve, Belgium

    Maxime Parmentier, Axel Legay & Firmin Chenoy

Authors
  1. Maxime Parmentier
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  2. Axel Legay
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  3. Firmin Chenoy
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Correspondence to Maxime Parmentier .

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Editors and Affiliations

  1. TU Dortmund University, Dortmund, Germany

    Bernhard Steffen

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Parmentier, M., Legay, A., Chenoy, F. (2024). Optimized Smart Sampling. In: Steffen, B. (eds) Bridging the Gap Between AI and Reality. AISoLA 2023. Lecture Notes in Computer Science, vol 14380. Springer, Cham. https://doi.org/10.1007/978-3-031-46002-9_10

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  • DOI: https://doi.org/10.1007/978-3-031-46002-9_10

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