35 Search Results for "Hunsberger, Luke"

Volume

LIPIcs, Volume 278

30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

TIME 2023, September 25-26, 2023, NCSR Demokritos, Athens, Greece

Editors: Alexander Artikis, Florian Bruse, and Luke Hunsberger

Document
DOI: 10.4230/LIPIcs.TIME.2025.11
A Better Algorithm for Converting an STNU into Minimal Dispatchable Form

Authors: Luke Hunsberger and Roberto Posenato

Published in: LIPIcs, Volume 355, 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)

Abstract
A Simple Temporal Network with Uncertainty (STNU) is a data structure for representing and reasoning about temporal constraints on activities, including those with uncertain durations. An STNU is dispatchable if it can be flexibly and efficiently executed in real time while guaranteeing that all relevant constraints are satisfied. Typically, dispatchability requires inserting conditional wait constraints, thereby forming an Extended STNU (ESTNU). The number of edges in an ESTNU affects the computational work that must be done during real-time execution. The MinDispESTNU problem is that of finding an equivalent dispatchable ESTNU having a minimal number of edges. Recent work presented an O(kn³)-time algorithm for solving the MinDispESTNU problem, where n is the number of timepoints and k is the number of actions with uncertain durations. A subsequent paper presented a faster O(n³)-time algorithm, but it has been shown to be incomplete. This paper presents a new O(mn+n²k+n²log n)-time algorithm for solving the MinDispESTNU problem, where m is the number of constraints in the network. The correctness of the algorithm is based on a novel theory of the canonical form of nested diamond structures. An empirical evaluation demonstrates the order-of-magnitude improvement in performance.
Cite as

Luke Hunsberger and Roberto Posenato. A Better Algorithm for Converting an STNU into Minimal Dispatchable Form. In 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 355, pp. 11:1-11:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hunsberger_et_al:LIPIcs.TIME.2025.11,
  author =	{Hunsberger, Luke and Posenato, Roberto},
  title =	{{A Better Algorithm for Converting an STNU into Minimal Dispatchable Form}},
  booktitle =	{32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)},
  pages =	{11:1--11:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-401-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{355},
  editor =	{Vidal, Thierry and Wa{\l}\k{e}ga, Przemys{\l}aw Andrzej},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2025.11},
  URN =		{urn:nbn:de:0030-drops-244578},
  doi =		{10.4230/LIPIcs.TIME.2025.11},
  annote =	{Keywords: Temporal constraint networks, dispatchable networks}
}
Document
DOI: 10.4230/LIPIcs.TIME.2024.9
A Faster Algorithm for Finding Negative Cycles in Simple Temporal Networks with Uncertainty

Authors: Luke Hunsberger and Roberto Posenato

Published in: LIPIcs, Volume 318, 31st International Symposium on Temporal Representation and Reasoning (TIME 2024)

Abstract
Temporal constraint networks are data structures for representing and reasoning about time (e.g., temporal constraints among actions in a plan). Finding and computing negative cycles in temporal networks is important for planning and scheduling applications since it is the first step toward resolving inconsistent networks. For Simple Temporal Networks (STNs), the problem reduces to finding simple negative cycles (i.e., no repeat nodes), resulting in numerous efficient algorithms. For Simple Temporal Networks with Uncertainty (STNUs), which accommodate actions with uncertain durations, the situation is more complex because the characteristic of a non-dynamically controllable (non-DC) network is a so-called semi-reducible negative (SRN) cycle, which can have repeat edges and, in the worst case, an exponential number of occurrences of such edges. Algorithms for computing SRN cycles in non-DC STNUs that have been presented so far are based on older, less efficient DC-checking algorithms. In addition, the issue of repeated edges has either been ignored or given scant attention. This paper presents a new, faster algorithm for identifying SRN cycles in non-DC STNUs. Its worst-case time complexity is O(mn + k²n + knlog n), where n is the number of timepoints, m is the number of constraints, and k is the number of actions with uncertain durations. This complexity is the same as that of the fastest DC-checking algorithm for STNUs. It avoids an exponential blow-up by efficiently dealing with repeated structures and outputting a compact representation of the SRN cycle it finds. The space required to compactly store accumulated path information while avoiding redundant storage of repeated edges is O(mk + k²n). An empirical evaluation demonstrates the effectiveness of the new algorithm on an existing benchmark.
Cite as

Luke Hunsberger and Roberto Posenato. A Faster Algorithm for Finding Negative Cycles in Simple Temporal Networks with Uncertainty. In 31st International Symposium on Temporal Representation and Reasoning (TIME 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 318, pp. 9:1-9:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{hunsberger_et_al:LIPIcs.TIME.2024.9,
  author =	{Hunsberger, Luke and Posenato, Roberto},
  title =	{{A Faster Algorithm for Finding Negative Cycles in Simple Temporal Networks with Uncertainty}},
  booktitle =	{31st International Symposium on Temporal Representation and Reasoning (TIME 2024)},
  pages =	{9:1--9:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-349-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{318},
  editor =	{Sala, Pietro and Sioutis, Michael and Wang, Fusheng},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2024.9},
  URN =		{urn:nbn:de:0030-drops-212160},
  doi =		{10.4230/LIPIcs.TIME.2024.9},
  annote =	{Keywords: Temporal constraint networks, overconstrained networks, negative cycles}
}
Document
DOI: 10.4230/LIPIcs.TIME.2024.11
Faster Algorithm for Converting an STNU into Minimal Dispatchable Form

Authors: Luke Hunsberger and Roberto Posenato

Published in: LIPIcs, Volume 318, 31st International Symposium on Temporal Representation and Reasoning (TIME 2024)

Abstract
A Simple Temporal Network with Uncertainty (STNU) is a data structure for representing and reasoning about temporal constraints on activities, including those with uncertain durations. An STNU is dispatchable if it can be flexibly and efficiently executed in real time while guaranteeing that all relevant constraints are satisfied. The number of edges in a dispatchable network affects the computational work that must be done during real-time execution. Recent work presented an O(k n³)-time algorithm for converting a dispatchable STNU into an equivalent dispatchable network having a minimal number of edges, where n is the number of timepoints and k is the number of actions with uncertain durations. This paper presents a modification of that algorithm, making it an order of magnitude faster, down to O(n³). Given that in typical applications k = O(n), this represents an effective order-of-magnitude reduction from O(n⁴) to O(n³).
Cite as

Luke Hunsberger and Roberto Posenato. Faster Algorithm for Converting an STNU into Minimal Dispatchable Form. In 31st International Symposium on Temporal Representation and Reasoning (TIME 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 318, pp. 11:1-11:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{hunsberger_et_al:LIPIcs.TIME.2024.11,
  author =	{Hunsberger, Luke and Posenato, Roberto},
  title =	{{Faster Algorithm for Converting an STNU into Minimal Dispatchable Form}},
  booktitle =	{31st International Symposium on Temporal Representation and Reasoning (TIME 2024)},
  pages =	{11:1--11:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-349-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{318},
  editor =	{Sala, Pietro and Sioutis, Michael and Wang, Fusheng},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2024.11},
  URN =		{urn:nbn:de:0030-drops-212182},
  doi =		{10.4230/LIPIcs.TIME.2024.11},
  annote =	{Keywords: Temporal constraint networks, dispatchable networks}
}
Document
DOI: 10.4230/LIPIcs.TIME.2024.12
Robust Execution of Probabilistic STNs

Authors: Luke Hunsberger and Roberto Posenato

Published in: LIPIcs, Volume 318, 31st International Symposium on Temporal Representation and Reasoning (TIME 2024)

Abstract
A Probabilistic Simple Temporal Network (PSTN) is a formalism for representing and reasoning about actions subject to temporal constraints, where some action durations may be uncontrollable, modeled using continuous probability density functions. Recent work aims to manage this kind of uncertainty during execution by approximating a PSTN by a Simple Temporal Network with Uncertainty (STNU) (for which well-known execution strategies exist) and using an STNU execution strategy to execute the PSTN, hoping that its probabilistic action durations will not cause any constraint violations. This paper presents significant improvements to the robust execution of PSTNs. Our approach is based on a recent, faster algorithm for finding negative cycles in non-DC STNUs. We also formally prove that many of the constraints included in others' work are unnecessary and that our algorithm can take advantage of a flexible real-time execution algorithm to react to observations of contingent durations that may fall outside the fixed STNU bounds. The paper presents an empirical evaluation of our approach that provides evidence of its effectiveness in robustly executing PSTNs derived from a publicly available benchmark.
Cite as

Luke Hunsberger and Roberto Posenato. Robust Execution of Probabilistic STNs. In 31st International Symposium on Temporal Representation and Reasoning (TIME 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 318, pp. 12:1-12:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{hunsberger_et_al:LIPIcs.TIME.2024.12,
  author =	{Hunsberger, Luke and Posenato, Roberto},
  title =	{{Robust Execution of Probabilistic STNs}},
  booktitle =	{31st International Symposium on Temporal Representation and Reasoning (TIME 2024)},
  pages =	{12:1--12:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-349-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{318},
  editor =	{Sala, Pietro and Sioutis, Michael and Wang, Fusheng},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2024.12},
  URN =		{urn:nbn:de:0030-drops-212197},
  doi =		{10.4230/LIPIcs.TIME.2024.12},
  annote =	{Keywords: Temporal constraint networks, probabilistic durations, dispatchable networks}
}
Document
Complete Volume
DOI: 10.4230/LIPIcs.TIME.2023
LIPIcs, Volume 278, TIME 2023, Complete Volume

Authors: Alexander Artikis, Florian Bruse, and Luke Hunsberger

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
LIPIcs, Volume 278, TIME 2023, Complete Volume
Cite as

30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 1-254, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@Proceedings{artikis_et_al:LIPIcs.TIME.2023,
  title =	{{LIPIcs, Volume 278, TIME 2023, Complete Volume}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{1--254},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023},
  URN =		{urn:nbn:de:0030-drops-190890},
  doi =		{10.4230/LIPIcs.TIME.2023},
  annote =	{Keywords: LIPIcs, Volume 278, TIME 2023, Complete Volume}
}
Document
Front Matter
DOI: 10.4230/LIPIcs.TIME.2023.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Alexander Artikis, Florian Bruse, and Luke Hunsberger

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as

30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 0:i-0:xiv, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{artikis_et_al:LIPIcs.TIME.2023.0,
  author =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{0:i--0:xiv},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.0},
  URN =		{urn:nbn:de:0030-drops-190907},
  doi =		{10.4230/LIPIcs.TIME.2023.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Invited Talk
DOI: 10.4230/LIPIcs.TIME.2023.1
Learning Temporal Logic Formulas from Time-Series Data (Invited Talk)

Authors: Laura Nenzi

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
In this talk, we provide an overview of recent advancements in the field of mining formal specifications from time-series data, with a specific focus on learning Signal Temporal Logic (STL) formulae.
Cite as

Laura Nenzi. Learning Temporal Logic Formulas from Time-Series Data (Invited Talk). In 30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 1:1-1:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{nenzi:LIPIcs.TIME.2023.1,
  author =	{Nenzi, Laura},
  title =	{{Learning Temporal Logic Formulas from Time-Series Data}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{1:1--1:2},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.1},
  URN =		{urn:nbn:de:0030-drops-190917},
  doi =		{10.4230/LIPIcs.TIME.2023.1},
  annote =	{Keywords: Temporal Logic, Mining Specifications}
}
Document
DOI: 10.4230/LIPIcs.TIME.2023.2
LTL over Finite Words Can Be Exponentially More Succinct Than Pure-Past LTL, and vice versa

Authors: Alessandro Artale, Luca Geatti, Nicola Gigante, Andrea Mazzullo, and Angelo Montanari

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
Linear Temporal Logic over finite traces (LTL_𝖿) has proved itself to be an important and effective formalism in formal verification as well as in artificial intelligence. Pure past LTL_𝖿 (pLTL) is the logic obtained from LTL_𝖿 by replacing each (future) temporal operator by a corresponding past one, and is naturally interpreted at the end of a finite trace. It is known that each property definable in LTL_𝖿 is also definable in pLTL, and ǐceversa. However, despite being extensively used in practice, to the best of our knowledge, there is no systematic study of their succinctness. In this paper, we investigate the succinctness of LTL_𝖿 and pLTL. First, we prove that pLTL can be exponentially more succinct than LTL_𝖿 by showing that there exists a property definable with a pLTL formula of size n such that the size of all LTL_𝖿 formulas defining it is at least exponential in n. Then, we prove that LTL_𝖿 can be exponentially more succinct than pLTL as well. This result shows that, although being expressively equivalent, LTL_𝖿 and pLTL are incomparable when succinctness is concerned. In addition, we study the succinctness of Safety-LTL (the syntactic safety fragment of LTL over infinite traces) with respect to its canonical form G(pLTL), whose formulas are of the form G(α), G being the globally operator and α a pLTL formula. We prove that G(pLTL) can be exponentially more succinct than Safety-LTL, and that the same holds for the dual cosafety fragment.
Cite as

Alessandro Artale, Luca Geatti, Nicola Gigante, Andrea Mazzullo, and Angelo Montanari. LTL over Finite Words Can Be Exponentially More Succinct Than Pure-Past LTL, and vice versa. In 30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 2:1-2:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{artale_et_al:LIPIcs.TIME.2023.2,
  author =	{Artale, Alessandro and Geatti, Luca and Gigante, Nicola and Mazzullo, Andrea and Montanari, Angelo},
  title =	{{LTL over Finite Words Can Be Exponentially More Succinct Than Pure-Past LTL, and vice versa}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{2:1--2:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.2},
  URN =		{urn:nbn:de:0030-drops-190927},
  doi =		{10.4230/LIPIcs.TIME.2023.2},
  annote =	{Keywords: Temporal Logic, Succinctness, LTLf, Finite Traces, Pure past LTL}
}
Document
DOI: 10.4230/LIPIcs.TIME.2023.3
LSCPM: Communities in Massive Real-World Link Streams by Clique Percolation Method

Authors: Alexis Baudin, Lionel Tabourier, and Clémence Magnien

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
Community detection is a popular approach to understand the organization of interactions in static networks. For that purpose, the Clique Percolation Method (CPM), which involves the percolation of k-cliques, is a well-studied technique that offers several advantages. Besides, studying interactions that occur over time is useful in various contexts, which can be modeled by the link stream formalism. The Dynamic Clique Percolation Method (DCPM) has been proposed for extending CPM to temporal networks. However, existing implementations are unable to handle massive datasets. We present a novel algorithm that adapts CPM to link streams, which has the advantage that it allows us to speed up the computation time with respect to the existing DCPM method. We evaluate it experimentally on real datasets and show that it scales to massive link streams. For example, it allows to obtain a complete set of communities in under twenty-five minutes for a dataset with thirty million links, what the state of the art fails to achieve even after a week of computation. We further show that our method provides communities similar to DCPM, but slightly more aggregated. We exhibit the relevance of the obtained communities in real world cases, and show that they provide information on the importance of vertices in the link streams.
Cite as

Alexis Baudin, Lionel Tabourier, and Clémence Magnien. LSCPM: Communities in Massive Real-World Link Streams by Clique Percolation Method. In 30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 3:1-3:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{baudin_et_al:LIPIcs.TIME.2023.3,
  author =	{Baudin, Alexis and Tabourier, Lionel and Magnien, Cl\'{e}mence},
  title =	{{LSCPM: Communities in Massive Real-World Link Streams by Clique Percolation Method}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{3:1--3:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.3},
  URN =		{urn:nbn:de:0030-drops-190932},
  doi =		{10.4230/LIPIcs.TIME.2023.3},
  annote =	{Keywords: Temporal network, Link stream, k-clique, Community detection, Clique Percolation Method, Real-world interactions}
}
Document
DOI: 10.4230/LIPIcs.TIME.2023.4
Discovering Predictive Dependencies on Multi-Temporal Relations

Authors: Beatrice Amico, Carlo Combi, Romeo Rizzi, and Pietro Sala

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
In this paper, we propose a methodology for deriving a new kind of approximate temporal functional dependencies, called Approximate Predictive Functional Dependencies (APFDs), based on a three-window framework and on a multi-temporal relational model. Different features are proposed for the Observation Window (OW), where we observe predictive data, for the Waiting Window (WW), and for the Prediction Window (PW), where the predicted event occurs. We then discuss the concept of approximation for such APFDs, introduce two new error measures. We prove that the problem of deriving APFDs is intractable. Moreover, we discuss some preliminary results in deriving APFDs from real clinical data using MIMIC III dataset, related to patients from Intensive Care Units.
Cite as

Beatrice Amico, Carlo Combi, Romeo Rizzi, and Pietro Sala. Discovering Predictive Dependencies on Multi-Temporal Relations. In 30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 4:1-4:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{amico_et_al:LIPIcs.TIME.2023.4,
  author =	{Amico, Beatrice and Combi, Carlo and Rizzi, Romeo and Sala, Pietro},
  title =	{{Discovering Predictive Dependencies on Multi-Temporal Relations}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{4:1--4:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.4},
  URN =		{urn:nbn:de:0030-drops-190945},
  doi =		{10.4230/LIPIcs.TIME.2023.4},
  annote =	{Keywords: temporal databases, temporal data mining, functional dependencies}
}
Document
DOI: 10.4230/LIPIcs.TIME.2023.5
Prime Scenarios in Qualitative Spatial and Temporal Reasoning

Authors: Yakoub Salhi and Michael Sioutis

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
The concept of prime implicant is a fundamental tool in Boolean algebra, which is used in Boolean circuit design and, recently, in explainable AI. This study investigates an analogous concept in qualitative spatial and temporal reasoning, called prime scenario. Specifically, we define a prime scenario of a qualitative constraint network (QCN) as a minimal set of decisions that can uniquely determine solutions of this QCN. We propose in this paper a collection of algorithms designed to address various problems related to prime scenarios. The first three algorithms aim to generate a prime scenario from a scenario of a QCN. The main idea consists in using path consistency to identify the constraints that can be ignored to generate a prime scenario. The next two algorithms focus on generating a set of prime scenarios that cover all the scenarios of the original QCN: The first algorithm examines every branch of the search tree, while the second is based on the use of a SAT encoding. Our last algorithm is concerned with computing a minimum-size prime scenario by using a MaxSAT encoding built from countermodels of the original QCN. We show that this algorithm is particularly useful for measuring the robustness of a QCN. Finally, a preliminary experimental evaluation is performed with instances of Allen’s Interval Algebra to assess the efficiency of our algorithms and, hence, also the difficulty of the newly introduced problems here.
Cite as

Yakoub Salhi and Michael Sioutis. Prime Scenarios in Qualitative Spatial and Temporal Reasoning. In 30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 5:1-5:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{salhi_et_al:LIPIcs.TIME.2023.5,
  author =	{Salhi, Yakoub and Sioutis, Michael},
  title =	{{Prime Scenarios in Qualitative Spatial and Temporal Reasoning}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{5:1--5:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.5},
  URN =		{urn:nbn:de:0030-drops-190957},
  doi =		{10.4230/LIPIcs.TIME.2023.5},
  annote =	{Keywords: Spatial and Temporal Reasoning, Qualitative Constraints, Prime Scenario, Prime Implicant, Robustness Measurement}
}
Document
DOI: 10.4230/LIPIcs.TIME.2023.6
Bounded-Memory Runtime Enforcement of Timed Properties

Authors: Saumya Shankar, Srinivas Pinisetty, and Thierry Jéron

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
Runtime Enforcement (RE) is a monitoring technique aimed at correcting possibly incorrect executions w.r.t. a set of formal requirements (properties) of a system. In this paper, we consider enforcement monitoring of real-time properties. Thus, executions are modelled as timed words and specifications as timed automata. Moreover, we consider that the enforcer has the ability to delay events by storing or buffering them into its internal memory (and releasing them when the property is finally satisfied) and suppressing events when no delaying is appropriate. Practically, in an implementation, the internal memory of the enforcer is finite. In this paper, we propose a new RE paradigm for timed properties, where the memory of the enforcer is bounded/finite, to address practical applications with memory constraints and timed specifications. Bounding the memory presents a number of difficulties, e.g., how to accommodate a timed event into the memory when the memory is full, s.t., regardless of the course of action we choose to handle this situation, the behaviour of the bounded enforcer should not significantly differ from that of the unbounded enforcer. The problem of how to optimally discard events when the buffer is full is significantly more difficult in a timed environment where the progress of time affects the satisfaction or violation of a property. We define the bounded-memory RE problem for timed properties and develop a framework for regular timed properties specified as timed automata. The proposed framework is implemented in Python, and its performance is evaluated. From experiments, we discovered that the enforcer has a reasonable execution time overhead.
Cite as

Saumya Shankar, Srinivas Pinisetty, and Thierry Jéron. Bounded-Memory Runtime Enforcement of Timed Properties. In 30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 6:1-6:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{shankar_et_al:LIPIcs.TIME.2023.6,
  author =	{Shankar, Saumya and Pinisetty, Srinivas and J\'{e}ron, Thierry},
  title =	{{Bounded-Memory Runtime Enforcement of Timed Properties}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{6:1--6:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.6},
  URN =		{urn:nbn:de:0030-drops-190962},
  doi =		{10.4230/LIPIcs.TIME.2023.6},
  annote =	{Keywords: Formal methods, Runtime enforcement, Bounded-memory, Timed automata}
}
Document
DOI: 10.4230/LIPIcs.TIME.2023.7
More Than 0s and 1s: Metric Quantifiers and Counting over Timed Words

Authors: Hsi-Ming Ho and Khushraj Madnani

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
We study the expressiveness of the pointwise interpretations (i.e. over timed words) of some predicate and temporal logics with metric and counting features. We show that counting in the unit interval (0, 1) is strictly weaker than counting in (0, b) with arbitrary b ≥ 0; moreover, allowing the latter indeed leads to expressive completeness for the metric predicate logic Q2MLO, recovering the corresponding result for the continuous interpretations (i.e. over signals). Exploiting this connection, we show that in contrast to the continuous case, adding "punctual" predicates into Q2MLO is still insufficient for the full expressive power of the Monadic First-Order Logic of Order and Metric (FO[<,+1]). Finally, we propose a generalisation of the recently proposed Pnueli automata modalities and show that the resulting metric temporal logic is expressively complete for FO[<,+1].
Cite as

Hsi-Ming Ho and Khushraj Madnani. More Than 0s and 1s: Metric Quantifiers and Counting over Timed Words. In 30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 7:1-7:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{ho_et_al:LIPIcs.TIME.2023.7,
  author =	{Ho, Hsi-Ming and Madnani, Khushraj},
  title =	{{More Than 0s and 1s: Metric Quantifiers and Counting over Timed Words}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{7:1--7:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.7},
  URN =		{urn:nbn:de:0030-drops-190979},
  doi =		{10.4230/LIPIcs.TIME.2023.7},
  annote =	{Keywords: Temporal Logic, Expressiveness, Automata}
}
Document
DOI: 10.4230/LIPIcs.TIME.2023.8
Analyzing Complex Systems with Cascades Using Continuous-Time Bayesian Networks

Authors: Alessandro Bregoli, Karin Rathsman, Marco Scutari, Fabio Stella, and Søren Wengel Mogensen

Published in: LIPIcs, Volume 278, 30th International Symposium on Temporal Representation and Reasoning (TIME 2023)

Abstract
Interacting systems of events may exhibit cascading behavior where events tend to be temporally clustered. While the cascades themselves may be obvious from the data, it is important to understand which states of the system trigger them. For this purpose, we propose a modeling framework based on continuous-time Bayesian networks (CTBNs) to analyze cascading behavior in complex systems. This framework allows us to describe how events propagate through the system and to identify likely sentry states, that is, system states that may lead to imminent cascading behavior. Moreover, CTBNs have a simple graphical representation and provide interpretable outputs, both of which are important when communicating with domain experts. We also develop new methods for knowledge extraction from CTBNs and we apply the proposed methodology to a data set of alarms in a large industrial system.
Cite as

Alessandro Bregoli, Karin Rathsman, Marco Scutari, Fabio Stella, and Søren Wengel Mogensen. Analyzing Complex Systems with Cascades Using Continuous-Time Bayesian Networks. In 30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 8:1-8:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{bregoli_et_al:LIPIcs.TIME.2023.8,
  author =	{Bregoli, Alessandro and Rathsman, Karin and Scutari, Marco and Stella, Fabio and Mogensen, S{\o}ren Wengel},
  title =	{{Analyzing Complex Systems with Cascades Using Continuous-Time Bayesian Networks}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{8:1--8:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-298-3},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{278},
  editor =	{Artikis, Alexander and Bruse, Florian and Hunsberger, Luke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2023.8},
  URN =		{urn:nbn:de:0030-drops-190980},
  doi =		{10.4230/LIPIcs.TIME.2023.8},
  annote =	{Keywords: event model, continuous-time Bayesian network, alarm network, graphical models, event cascade}
}
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