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Documents authored by Ye, Lina

Document
DOI: 10.4230/LIPIcs.CONCUR.2023.14
About Decisiveness of Dynamic Probabilistic Models

Authors: Alain Finkel, Serge Haddad, and Lina Ye

Published in: LIPIcs, Volume 279, 34th International Conference on Concurrency Theory (CONCUR 2023)

Abstract
Decisiveness of infinite Markov chains with respect to some (finite or infinite) target set of states is a key property that allows to compute the reachability probability of this set up to an arbitrary precision. Most of the existing works assume constant weights for defining the probability of a transition in the considered models. However numerous probabilistic modelings require the (dynamic) weight to also depend on the current state. So we introduce a dynamic probabilistic version of counter machine (pCM). After establishing that decisiveness is undecidable for pCMs even with constant weights, we study the decidability of decisiveness for subclasses of pCM. We show that, without restrictions on dynamic weights, decisiveness is undecidable with a single state and single counter pCM. On the contrary with polynomial weights, decisiveness becomes decidable for single counter pCMs under mild conditions. Then we show that decisiveness of probabilistic Petri nets (pPNs) with polynomial weights is undecidable even when the target set is upward-closed unlike the case of constant weights. Finally we prove that the standard subclass of pPNs with a regular language is decisive with respect to a finite set whatever the kind of weights.
Cite as

Alain Finkel, Serge Haddad, and Lina Ye. About Decisiveness of Dynamic Probabilistic Models. In 34th International Conference on Concurrency Theory (CONCUR 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 279, pp. 14:1-14:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{finkel_et_al:LIPIcs.CONCUR.2023.14,
  author =	{Finkel, Alain and Haddad, Serge and Ye, Lina},
  title =	{{About Decisiveness of Dynamic Probabilistic Models}},
  booktitle =	{34th International Conference on Concurrency Theory (CONCUR 2023)},
  pages =	{14:1--14:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-299-0},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{279},
  editor =	{P\'{e}rez, Guillermo A. and Raskin, Jean-Fran\c{c}ois},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CONCUR.2023.14},
  URN =		{urn:nbn:de:0030-drops-190089},
  doi =		{10.4230/LIPIcs.CONCUR.2023.14},
  annote =	{Keywords: infinite Markov chain, reachability probability, decisiveness}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2020.48
Active Prediction for Discrete Event Systems

Authors: Stefan Haar, Serge Haddad, Stefan Schwoon, and Lina Ye

Published in: LIPIcs, Volume 182, 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020)

Abstract
A central task in partially observed controllable system is to detect or prevent the occurrence of certain events called faults. Systems for which one can design a controller avoiding the faults are called actively safe. Otherwise, one may require that a fault is eventually detected, which is the task of diagnosis. Systems for which one can design a controller detecting the faults are called actively diagnosable. An intermediate requirement is prediction, which consists in determining that a fault will occur whatever the future behaviour of the system. When a system is not predictable, one may be interested in designing a controller to make it so. Here we study the latter problem, called active prediction, and its associated property, active predictability. In other words, we investigate how to determine whether or not a system enjoys the active predictability property, i.e., there exists an active predictor for the system. Our contributions are threefold. From a semantical point of view, we refine the notion of predictability by adding two quantitative requirements: the minimal and maximal delay before the occurence of the fault, and we characterize the requirements fulfilled by a controller that performs predictions. Then we show that active predictability is EXPTIME-complete where the upper bound is obtained via a game-based approach. Finally we establish that active predictability is equivalent to active safety when the maximal delay is beyond a threshold depending on the size of the system, and we show that this threshold is accurate by exhibiting a family of systems fulfilling active predictability but not active safety.
Cite as

Stefan Haar, Serge Haddad, Stefan Schwoon, and Lina Ye. Active Prediction for Discrete Event Systems. In 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 182, pp. 48:1-48:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{haar_et_al:LIPIcs.FSTTCS.2020.48,
  author =	{Haar, Stefan and Haddad, Serge and Schwoon, Stefan and Ye, Lina},
  title =	{{Active Prediction for Discrete Event Systems}},
  booktitle =	{40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020)},
  pages =	{48:1--48:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-174-0},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{182},
  editor =	{Saxena, Nitin and Simon, Sunil},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2020.48},
  URN =		{urn:nbn:de:0030-drops-132898},
  doi =		{10.4230/LIPIcs.FSTTCS.2020.48},
  annote =	{Keywords: Automata Theory, Partially observed systems, Diagnosability, Predictability}
}
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