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Documents authored by Sciavicco, Guido

Document
Invited Talk
DOI: 10.4230/LIPIcs.TIME.2024.1
A General Logical Approach to Learning from Time Series (Invited Talk)

Authors: Guido Sciavicco

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

Abstract
Machine learning from multivariate time series is a common task, and countless different approaches to typical learning problems have been proposed in recent years. In this talk, we review some basic ideas towards logic-based learning methods, and we sketch a general framework.
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Guido Sciavicco. A General Logical Approach to Learning from Time Series (Invited Talk). In 31st International Symposium on Temporal Representation and Reasoning (TIME 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 318, pp. 1:1-1:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{sciavicco:LIPIcs.TIME.2024.1,
  author =	{Sciavicco, Guido},
  title =	{{A General Logical Approach to Learning from Time Series}},
  booktitle =	{31st International Symposium on Temporal Representation and Reasoning (TIME 2024)},
  pages =	{1:1--1:2},
  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.2024.1},
  URN =		{urn:nbn:de:0030-drops-212088},
  doi =		{10.4230/LIPIcs.TIME.2024.1},
  annote =	{Keywords: Machine learning, temporal logic, general approach}
}
Document
DOI: 10.4230/LIPIcs.TIME.2024.7
Fitting’s Style Many-Valued Interval Temporal Logic Tableau System: Theory and Implementation

Authors: Guillermo Badia, Carles Noguera, Alberto Paparella, Guido Sciavicco, and Ionel Eduard Stan

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

Abstract
Many-valued logics, often referred to as fuzzy logics, are a fundamental tool for reasoning about uncertainty, and are based on truth value algebras that generalize the Boolean one; the same logic can be interpreted on algebras from different varieties, for different purposes and pose different challenges. Although temporal many-valued logics, that is, the many-valued counterpart of popular temporal logics, have received little attention in the literature, the many-valued generalization of Halpern and Shoham’s interval temporal logic has been recently introduced and studied, and a sound and complete tableau system for it has been presented for the case in which it is interpreted on some finite Heyting algebra. In this paper, we take a step further in this inquiry by exploring a tableau system for Halpern and Shoham’s interval temporal logic interpreted on some finite {FL_{ew}}-algebra, therefore generalizing the Heyting case, and by providing its open-source implementation.
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Guillermo Badia, Carles Noguera, Alberto Paparella, Guido Sciavicco, and Ionel Eduard Stan. Fitting’s Style Many-Valued Interval Temporal Logic Tableau System: Theory and Implementation. In 31st International Symposium on Temporal Representation and Reasoning (TIME 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 318, pp. 7:1-7:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{badia_et_al:LIPIcs.TIME.2024.7,
  author =	{Badia, Guillermo and Noguera, Carles and Paparella, Alberto and Sciavicco, Guido and Stan, Ionel Eduard},
  title =	{{Fitting’s Style Many-Valued Interval Temporal Logic Tableau System: Theory and Implementation}},
  booktitle =	{31st International Symposium on Temporal Representation and Reasoning (TIME 2024)},
  pages =	{7:1--7:16},
  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.2024.7},
  URN =		{urn:nbn:de:0030-drops-212145},
  doi =		{10.4230/LIPIcs.TIME.2024.7},
  annote =	{Keywords: Interval temporal logic, many-valued logic, tableau system}
}
Document
DOI: 10.4230/LIPIcs.TIME.2023.9
A Sound and Complete Tableau System for Fuzzy Halpern and Shoham’s Interval Temporal Logic

Authors: Willem Conradie, Riccardo Monego, Emilio Muñoz-Velasco, Guido Sciavicco, and Ionel Eduard Stan

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

Abstract
Interval temporal logic plays a critical role in various applications, including planning, scheduling, and formal verification; recently, interval temporal logic has also been successfully applied to learning from temporal data. Halpern and Shoham’s interval temporal logic, in particular, stands out as a very intuitive, yet expressive, interval-based formalism. To address real-world scenarios involving uncertainty and imprecision, Halpern and Shoham’s logic has been recently generalized to the fuzzy (many-valued) case. The resulting language capitalizes on many-valued modal logics, allowing for a range of truth values that reflect multiple expert perspectives, but inherits the bad computational behaviour of its crisp counterpart. In this work, we investigate a sound and complete tableau system for fuzzy Halpern and Shoham’s logic, which, although possibly non-terminating, offers a semi-decision procedure for the finite case.
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Willem Conradie, Riccardo Monego, Emilio Muñoz-Velasco, Guido Sciavicco, and Ionel Eduard Stan. A Sound and Complete Tableau System for Fuzzy Halpern and Shoham’s Interval Temporal Logic. In 30th International Symposium on Temporal Representation and Reasoning (TIME 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 278, pp. 9:1-9:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{conradie_et_al:LIPIcs.TIME.2023.9,
  author =	{Conradie, Willem and Monego, Riccardo and Mu\~{n}oz-Velasco, Emilio and Sciavicco, Guido and Stan, Ionel Eduard},
  title =	{{A Sound and Complete Tableau System for Fuzzy Halpern and Shoham’s Interval Temporal Logic}},
  booktitle =	{30th International Symposium on Temporal Representation and Reasoning (TIME 2023)},
  pages =	{9:1--9:14},
  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.2023.9},
  URN =		{urn:nbn:de:0030-drops-190996},
  doi =		{10.4230/LIPIcs.TIME.2023.9},
  annote =	{Keywords: Interval temporal logic, many-valued logic, tableau system}
}
Document
DOI: 10.4230/LIPIcs.TIME.2022.13
Neural-Symbolic Temporal Decision Trees for Multivariate Time Series Classification

Authors: Giovanni Pagliarini, Simone Scaboro, Giuseppe Serra, Guido Sciavicco, and Ionel Eduard Stan

Published in: LIPIcs, Volume 247, 29th International Symposium on Temporal Representation and Reasoning (TIME 2022)

Abstract
Multivariate time series classification is a widely known problem, and its applications are ubiquitous. Due to their strong generalization capability, neural networks have been proven to be very powerful for the task, but their applicability is often limited by their intrinsic black-box nature. Recently, temporal decision trees have been shown to be a serious alternative to neural networks for the same task in terms of classification performances, while attaining higher levels of transparency and interpretability. In this work, we propose an initial approach to neural-symbolic temporal decision trees, that is, an hybrid method that leverages on both the ability of neural networks of capturing temporal patterns and the flexibility of temporal decision trees of taking decisions on intervals based on (possibly, externally computed) temporal features. While based on a proof-of-concept implementation, in our experiments on public datasets, neural-symbolic temporal decision trees show promising results.
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Giovanni Pagliarini, Simone Scaboro, Giuseppe Serra, Guido Sciavicco, and Ionel Eduard Stan. Neural-Symbolic Temporal Decision Trees for Multivariate Time Series Classification. In 29th International Symposium on Temporal Representation and Reasoning (TIME 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 247, pp. 13:1-13:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{pagliarini_et_al:LIPIcs.TIME.2022.13,
  author =	{Pagliarini, Giovanni and Scaboro, Simone and Serra, Giuseppe and Sciavicco, Guido and Stan, Ionel Eduard},
  title =	{{Neural-Symbolic Temporal Decision Trees for Multivariate Time Series Classification}},
  booktitle =	{29th International Symposium on Temporal Representation and Reasoning (TIME 2022)},
  pages =	{13:1--13:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-262-4},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{247},
  editor =	{Artikis, Alexander and Posenato, Roberto and Tonetta, Stefano},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2022.13},
  URN =		{urn:nbn:de:0030-drops-172607},
  doi =		{10.4230/LIPIcs.TIME.2022.13},
  annote =	{Keywords: Machine learning, neural-symbolic, temporal logic, hybrid temporal decision trees}
}
Document
DOI: 10.4230/LIPIcs.TIME.2021.7
Interval Temporal Random Forests with an Application to COVID-19 Diagnosis

Authors: Federico Manzella, Giovanni Pagliarini, Guido Sciavicco, and Ionel Eduard Stan

Published in: LIPIcs, Volume 206, 28th International Symposium on Temporal Representation and Reasoning (TIME 2021)

Abstract
Symbolic learning is the logic-based approach to machine learning. The mission of symbolic learning is to provide algorithms and methodologies to extract logical information from data and express it in an interpretable way. In the context of temporal data, interval temporal logic has been recently proposed as a suitable tool for symbolic learning, specifically via the design of an interval temporal logic decision tree extraction algorithm. Building on it, we study here its natural generalization to interval temporal random forests, mimicking the corresponding schema at the propositional level. Interval temporal random forests turn out to be a very performing multivariate time series classification method, which, despite the introduction of a functional component, are still logically interpretable to some extent. We apply this method to the problem of diagnosing COVID-19 based on the time series that emerge from cough and breath recording of positive versus negative subjects. Our experiment show that our models achieve very high accuracies and sensitivities, often superior to those achieved by classical methods on the same data. Although other recent approaches to the same problem (based on different and more numerous data) show even better statistical results, our solution is the first logic-based, interpretable, and explainable one.
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Federico Manzella, Giovanni Pagliarini, Guido Sciavicco, and Ionel Eduard Stan. Interval Temporal Random Forests with an Application to COVID-19 Diagnosis. In 28th International Symposium on Temporal Representation and Reasoning (TIME 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 206, pp. 7:1-7:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{manzella_et_al:LIPIcs.TIME.2021.7,
  author =	{Manzella, Federico and Pagliarini, Giovanni and Sciavicco, Guido and Stan, Ionel Eduard},
  title =	{{Interval Temporal Random Forests with an Application to COVID-19 Diagnosis}},
  booktitle =	{28th International Symposium on Temporal Representation and Reasoning (TIME 2021)},
  pages =	{7:1--7:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-206-8},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{206},
  editor =	{Combi, Carlo and Eder, Johann and Reynolds, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2021.7},
  URN =		{urn:nbn:de:0030-drops-147837},
  doi =		{10.4230/LIPIcs.TIME.2021.7},
  annote =	{Keywords: Interval temporal logic, decision trees, random forests, sound-based diagnosis}
}
Document
DOI: 10.4230/LIPIcs.TIME.2020.5
The Horn Fragment of Branching Algebra

Authors: Alessandro Bertagnon, Marco Gavanelli, Alessandro Passantino, Guido Sciavicco, and Stefano Trevisani

Published in: LIPIcs, Volume 178, 27th International Symposium on Temporal Representation and Reasoning (TIME 2020)

Abstract
Branching Algebra is the natural branching-time generalization of Allen’s Interval Algebra. As in the linear case, the consistency problem for Branching Algebra is NP-hard. Being relatively new, however, not much is known about the computational behaviour of the consistency problem of its sub-algebras, except in the case of the recently found subset of convex branching relations, for which the consistency of a network can be tested via path consistency and it is therefore deterministic polynomial. In this paper, following Nebel and Bürckert, we define the Horn fragment of Branching Algebra, and prove that it is a sub-algebra of the latter, being closed under inverse, intersection, and composition, that it strictly contains both the convex fragment of Branching Algebra and the Horn fragment of Interval Algebra, and that its consistency problem can be decided via path consistency. Finally, we experimentally prove that the Horn fragment of Branching Algebra can be used as an heuristic for checking the consistency of a generic network with a considerable improvement over the convex subset.
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Alessandro Bertagnon, Marco Gavanelli, Alessandro Passantino, Guido Sciavicco, and Stefano Trevisani. The Horn Fragment of Branching Algebra. In 27th International Symposium on Temporal Representation and Reasoning (TIME 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 178, pp. 5:1-5:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{bertagnon_et_al:LIPIcs.TIME.2020.5,
  author =	{Bertagnon, Alessandro and Gavanelli, Marco and Passantino, Alessandro and Sciavicco, Guido and Trevisani, Stefano},
  title =	{{The Horn Fragment of Branching Algebra}},
  booktitle =	{27th International Symposium on Temporal Representation and Reasoning (TIME 2020)},
  pages =	{5:1--5:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-167-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{178},
  editor =	{Mu\~{n}oz-Velasco, Emilio and Ozaki, Ana and Theobald, Martin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2020.5},
  URN =		{urn:nbn:de:0030-drops-129736},
  doi =		{10.4230/LIPIcs.TIME.2020.5},
  annote =	{Keywords: Constraint programming, Consistency, Branching time, Horn Fragment}
}
Document
DOI: 10.4230/LIPIcs.TIME.2020.9
Knowledge Extraction with Interval Temporal Logic Decision Trees

Authors: Guido Sciavicco and Ionel Eduard Stan

Published in: LIPIcs, Volume 178, 27th International Symposium on Temporal Representation and Reasoning (TIME 2020)

Abstract
Multivariate temporal, or time, series classification is, in a way, the temporal generalization of (numeric) classification, as every instance is described by multiple time series instead of multiple values. Symbolic classification is the machine learning strategy to extract explicit knowledge from a data set, and the problem of symbolic classification of multivariate temporal series requires the design, implementation, and test of ad-hoc machine learning algorithms, such as, for example, algorithms for the extraction of temporal versions of decision trees. One of the most well-known algorithms for decision tree extraction from categorical data is Quinlan’s ID3, which was later extended to deal with numerical attributes, resulting in an algorithm known as C4.5, and implemented in many open-sources data mining libraries, including the so-called Weka, which features an implementation of C4.5 called J48. ID3 was recently generalized to deal with temporal data in form of timelines, which can be seen as discrete (categorical) versions of multivariate time series, and such a generalization, based on the interval temporal logic HS, is known as Temporal ID3. In this paper we introduce Temporal C4.5, that allows the extraction of temporal decision trees from undiscretized multivariate time series, describe its implementation, called Temporal J48, and discuss the outcome of a set of experiments with the latter on a collection of public data sets, comparing the results with those obtained by other, classical, multivariate time series classification methods.
Cite as

Guido Sciavicco and Ionel Eduard Stan. Knowledge Extraction with Interval Temporal Logic Decision Trees. In 27th International Symposium on Temporal Representation and Reasoning (TIME 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 178, pp. 9:1-9:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{sciavicco_et_al:LIPIcs.TIME.2020.9,
  author =	{Sciavicco, Guido and Stan, Ionel Eduard},
  title =	{{Knowledge Extraction with Interval Temporal Logic Decision Trees}},
  booktitle =	{27th International Symposium on Temporal Representation and Reasoning (TIME 2020)},
  pages =	{9:1--9:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-167-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{178},
  editor =	{Mu\~{n}oz-Velasco, Emilio and Ozaki, Ana and Theobald, Martin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2020.9},
  URN =		{urn:nbn:de:0030-drops-129776},
  doi =		{10.4230/LIPIcs.TIME.2020.9},
  annote =	{Keywords: Interval Temporal Logic, Decision Trees, Explainable AI, Time series}
}
Document
DOI: 10.4230/LIPIcs.TIME.2020.11
Mining Significant Temporal Networks Is Polynomial

Authors: Guido Sciavicco, Matteo Zavatteri, and Tiziano Villa

Published in: LIPIcs, Volume 178, 27th International Symposium on Temporal Representation and Reasoning (TIME 2020)

Abstract
A Conditional Simple Temporal Network with Uncertainty and Decisions (CSTNUD) is a formalism that tackles controllable and uncontrollable durations as well as controllable and uncontrollable choices simultaneously. In the classic top-down model-based engineering approach, a designer builds a CSTNUD to model, validate and execute some temporal plan of interest. Instead, in this paper, we investigate the bottom-up approach by providing a deterministic polynomial time algorithm to mine a CSTNUD from a set of execution traces (i.e., a log). This paper paves the way for the design of controllable temporal networks mined from traces that also contain information on uncontrollable events.
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Guido Sciavicco, Matteo Zavatteri, and Tiziano Villa. Mining Significant Temporal Networks Is Polynomial. In 27th International Symposium on Temporal Representation and Reasoning (TIME 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 178, pp. 11:1-11:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{sciavicco_et_al:LIPIcs.TIME.2020.11,
  author =	{Sciavicco, Guido and Zavatteri, Matteo and Villa, Tiziano},
  title =	{{Mining Significant Temporal Networks Is Polynomial}},
  booktitle =	{27th International Symposium on Temporal Representation and Reasoning (TIME 2020)},
  pages =	{11:1--11:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-167-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{178},
  editor =	{Mu\~{n}oz-Velasco, Emilio and Ozaki, Ana and Theobald, Martin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2020.11},
  URN =		{urn:nbn:de:0030-drops-129792},
  doi =		{10.4230/LIPIcs.TIME.2020.11},
  annote =	{Keywords: Mining temporal constraints, cstnud, uncertainty, significant temporal network}
}
Document
Complete Volume
DOI: 10.4230/LIPIcs.TIME.2019
LIPIcs, Volume 147, TIME'19, Complete Volume

Authors: Johann Gamper, Sophie Pinchinat, and Guido Sciavicco

Published in: LIPIcs, Volume 147, 26th International Symposium on Temporal Representation and Reasoning (TIME 2019)

Abstract
LIPIcs, Volume 147, TIME'19, Complete Volume
Cite as

26th International Symposium on Temporal Representation and Reasoning (TIME 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 147, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@Proceedings{gamper_et_al:LIPIcs.TIME.2019,
  title =	{{LIPIcs, Volume 147, TIME'19, Complete Volume}},
  booktitle =	{26th International Symposium on Temporal Representation and Reasoning (TIME 2019)},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-127-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{147},
  editor =	{Gamper, Johann and Pinchinat, Sophie and Sciavicco, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2019},
  URN =		{urn:nbn:de:0030-drops-113887},
  doi =		{10.4230/LIPIcs.TIME.2019},
  annote =	{Keywords: Theory of computation, Logic; Information systems, Temporal data; Computing methodologies, Knowledge representation and reasoning}
}
Document
Front Matter
DOI: 10.4230/LIPIcs.TIME.2019.0
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Johann Gamper, Sophie Pinchinat, and Guido Sciavicco

Published in: LIPIcs, Volume 147, 26th International Symposium on Temporal Representation and Reasoning (TIME 2019)

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

26th International Symposium on Temporal Representation and Reasoning (TIME 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 147, pp. 0:i-0:xiv, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{gamper_et_al:LIPIcs.TIME.2019.0,
  author =	{Gamper, Johann and Pinchinat, Sophie and Sciavicco, Guido},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  booktitle =	{26th International Symposium on Temporal Representation and Reasoning (TIME 2019)},
  pages =	{0:i--0:xiv},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-127-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{147},
  editor =	{Gamper, Johann and Pinchinat, Sophie and Sciavicco, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2019.0},
  URN =		{urn:nbn:de:0030-drops-113582},
  doi =		{10.4230/LIPIcs.TIME.2019.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
DOI: 10.4230/LIPIcs.TIME.2018.7
Extracting Interval Temporal Logic Rules: A First Approach

Authors: Davide Bresolin, Enrico Cominato, Simone Gnani, Emilio Muñoz-Velasco, and Guido Sciavicco

Published in: LIPIcs, Volume 120, 25th International Symposium on Temporal Representation and Reasoning (TIME 2018)

Abstract
Discovering association rules is a classical data mining task with a wide range of applications that include the medical, the financial, and the planning domains, among others. Modern rule extraction algorithms focus on static rules, typically expressed in the language of Horn propositional logic, as opposed to temporal ones, which have received less attention in the literature. Since in many application domains temporal information is stored in form of intervals, extracting interval-based temporal rules seems the natural choice. In this paper we extend the well-known algorithm APRIORI for rule extraction to discover interval temporal rules written in the Horn fragment of Halpern and Shoham's interval temporal logic.
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Davide Bresolin, Enrico Cominato, Simone Gnani, Emilio Muñoz-Velasco, and Guido Sciavicco. Extracting Interval Temporal Logic Rules: A First Approach. In 25th International Symposium on Temporal Representation and Reasoning (TIME 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 120, pp. 7:1-7:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{bresolin_et_al:LIPIcs.TIME.2018.7,
  author =	{Bresolin, Davide and Cominato, Enrico and Gnani, Simone and Mu\~{n}oz-Velasco, Emilio and Sciavicco, Guido},
  title =	{{Extracting Interval Temporal Logic Rules: A First Approach}},
  booktitle =	{25th International Symposium on Temporal Representation and Reasoning (TIME 2018)},
  pages =	{7:1--7:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-089-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{120},
  editor =	{Alechina, Natasha and N{\o}rv\r{a}g, Kjetil and Penczek, Wojciech},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2018.7},
  URN =		{urn:nbn:de:0030-drops-97728},
  doi =		{10.4230/LIPIcs.TIME.2018.7},
  annote =	{Keywords: Interval temporal logic, Horn fragment, Rule extraction}
}
Document
DOI: 10.4230/LIPIcs.TIME.2018.12
Deciding the Consistency of Branching Time Interval Networks

Authors: Marco Gavanelli, Alessandro Passantino, and Guido Sciavicco

Published in: LIPIcs, Volume 120, 25th International Symposium on Temporal Representation and Reasoning (TIME 2018)

Abstract
Allen's Interval Algebra (IA) is one of the most prominent formalisms in the area of qualitative temporal reasoning; however, its applications are naturally restricted to linear flows of time. When dealing with nonlinear time, Allen's algebra can be extended in several ways, and, as suggested by Ragni and Wölfl [M. Ragni and S. Wölfl, 2004], a possible solution consists in defining the Branching Algebra (BA) as a set of 19 basic relations (13 basic linear relations plus 6 new basic nonlinear ones) in such a way that each basic relation between two intervals is completely defined by the relative position of the endpoints on a tree-like partial order. While the problem of deciding the consistency of a network of IA-constraints is well-studied, and every subset of the IA has been classified with respect to the tractability of its consistency problem, the fragments of the BA have received less attention. In this paper, we first define the notion of convex BA-relation, and, then, we prove that the consistency of a network of convex BA-relations can be decided via path consistency, and is therefore a polynomial problem. This is the first non-trivial tractable fragment of the BA; given the clear parallel with the linear case, our contribution poses the bases for a deeper study of fragments of BA towards their complete classification.
Cite as

Marco Gavanelli, Alessandro Passantino, and Guido Sciavicco. Deciding the Consistency of Branching Time Interval Networks. In 25th International Symposium on Temporal Representation and Reasoning (TIME 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 120, pp. 12:1-12:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{gavanelli_et_al:LIPIcs.TIME.2018.12,
  author =	{Gavanelli, Marco and Passantino, Alessandro and Sciavicco, Guido},
  title =	{{Deciding the Consistency of Branching Time Interval Networks}},
  booktitle =	{25th International Symposium on Temporal Representation and Reasoning (TIME 2018)},
  pages =	{12:1--12:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-089-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{120},
  editor =	{Alechina, Natasha and N{\o}rv\r{a}g, Kjetil and Penczek, Wojciech},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2018.12},
  URN =		{urn:nbn:de:0030-drops-97779},
  doi =		{10.4230/LIPIcs.TIME.2018.12},
  annote =	{Keywords: Constraint programming, Consistency, Branching time}
}
Document
DOI: 10.4230/LIPIcs.TIME.2017.11
Evaluation of Temporal Datasets via Interval Temporal Logic Model Checking

Authors: Dario Della Monica, David de Frutos-Escrig, Angelo Montanari, Aniello Murano, and Guido Sciavicco

Published in: LIPIcs, Volume 90, 24th International Symposium on Temporal Representation and Reasoning (TIME 2017)

Abstract
The problem of temporal dataset evaluation consists in establishing to what extent a set of temporal data (histories) complies with a given temporal condition. It presents a strong resemblance with the problem of model checking enhanced with the ability of rating the compliance degree of a model against a formula. In this paper, we solve the temporal dataset evaluation problem by suitably combining the outcomes of model checking an interval temporal logic formula against sets of histories (finite interval models), possibly taking into account domain-dependent measures/criteria, like, for instance, sensitivity, specificity, and accuracy. From a technical point of view, the main contribution of the paper is a (deterministic) polynomial time algorithm for interval temporal logic model checking over finite interval models. To the best of our knowledge, this is the first application of a (truly) interval temporal logic model checking in the area of temporal databases and data mining rather than in the formal verification setting.
Cite as

Dario Della Monica, David de Frutos-Escrig, Angelo Montanari, Aniello Murano, and Guido Sciavicco. Evaluation of Temporal Datasets via Interval Temporal Logic Model Checking. In 24th International Symposium on Temporal Representation and Reasoning (TIME 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 90, pp. 11:1-11:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{dellamonica_et_al:LIPIcs.TIME.2017.11,
  author =	{Della Monica, Dario and de Frutos-Escrig, David and Montanari, Angelo and Murano, Aniello and Sciavicco, Guido},
  title =	{{Evaluation of Temporal Datasets via Interval Temporal Logic Model Checking}},
  booktitle =	{24th International Symposium on Temporal Representation and Reasoning (TIME 2017)},
  pages =	{11:1--11:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-052-1},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{90},
  editor =	{Schewe, Sven and Schneider, Thomas and Wijsen, Jef},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.TIME.2017.11},
  URN =		{urn:nbn:de:0030-drops-79280},
  doi =		{10.4230/LIPIcs.TIME.2017.11},
  annote =	{Keywords: Dataset Evaluation, Temporal Databases, Model Checking, Interval Temporal Logics}
}
Document
DOI: 10.4230/LIPIcs.CSL.2017.17
Fast(er) Reasoning in Interval Temporal Logic

Authors: Davide Bresolin, Emilio Muñoz-Velasco, and Guido Sciavicco

Published in: LIPIcs, Volume 82, 26th EACSL Annual Conference on Computer Science Logic (CSL 2017)

Abstract
Clausal forms of logics are of great relevance in Artificial Intelligence, because they couple a high expressivity with a low complexity of reasoning problems. They have been studied for a wide range of classical, modal and temporal logics to obtain tractable fragments of intractable formalisms. In this paper we show that such restrictions can be exploited to lower the complexity of interval temporal logics as well. In particular, we show that for the Horn fragment of the interval logic AAbar (that is, the logic with the modal operators for Allen’s relations meets and met by) without diamonds the complexity lowers from NEXPTIME-complete to P-complete. We prove also that the tractability of the Horn fragments of interval temporal logics is lost as soon as other interval temporal operators are added to AAbar, in most of the cases.
Cite as

Davide Bresolin, Emilio Muñoz-Velasco, and Guido Sciavicco. Fast(er) Reasoning in Interval Temporal Logic. In 26th EACSL Annual Conference on Computer Science Logic (CSL 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 82, pp. 17:1-17:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{bresolin_et_al:LIPIcs.CSL.2017.17,
  author =	{Bresolin, Davide and Mu\~{n}oz-Velasco, Emilio and Sciavicco, Guido},
  title =	{{Fast(er) Reasoning in Interval Temporal Logic}},
  booktitle =	{26th EACSL Annual Conference on Computer Science Logic (CSL 2017)},
  pages =	{17:1--17:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-045-3},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{82},
  editor =	{Goranko, Valentin and Dam, Mads},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CSL.2017.17},
  URN =		{urn:nbn:de:0030-drops-76782},
  doi =		{10.4230/LIPIcs.CSL.2017.17},
  annote =	{Keywords: Temporal Logic, Horn Fragments, Satisfiability, Complexity}
}
Document
DOI: 10.4230/LIPIcs.STACS.2010.2488
Decidability of the Interval Temporal Logic ABB over the Natural Numbers

Authors: Angelo Montanari, Gabriele Puppis, Pietro Sala, and Guido Sciavicco

Published in: LIPIcs, Volume 5, 27th International Symposium on Theoretical Aspects of Computer Science (2010)

Abstract
In this paper, we focus our attention on the interval temporal logic of the Allen's relations ``meets'', ``begins'', and ``begun by'' ($\ABB$ for short), interpreted over natural numbers. We first introduce the logic and we show that it is expressive enough to model distinctive interval properties, such as accomplishment conditions, to capture basic modalities of point-based temporal logic, such as the until operator, and to encode relevant metric constraints. Then, we prove that the satisfiability problem for $\ABB$ over natural numbers is decidable by providing a small model theorem based on an original contraction method. Finally, we prove the EXPSPACE-completeness of the problem.
Cite as

Angelo Montanari, Gabriele Puppis, Pietro Sala, and Guido Sciavicco. Decidability of the Interval Temporal Logic ABB over the Natural Numbers. In 27th International Symposium on Theoretical Aspects of Computer Science. Leibniz International Proceedings in Informatics (LIPIcs), Volume 5, pp. 597-608, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2010)

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@InProceedings{montanari_et_al:LIPIcs.STACS.2010.2488,
  author =	{Montanari, Angelo and Puppis, Gabriele and Sala, Pietro and Sciavicco, Guido},
  title =	{{Decidability of the Interval Temporal Logic ABB over the Natural Numbers}},
  booktitle =	{27th International Symposium on Theoretical Aspects of Computer Science},
  pages =	{597--608},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-16-3},
  ISSN =	{1868-8969},
  year =	{2010},
  volume =	{5},
  editor =	{Marion, Jean-Yves and Schwentick, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2010.2488},
  URN =		{urn:nbn:de:0030-drops-24884},
  doi =		{10.4230/LIPIcs.STACS.2010.2488},
  annote =	{Keywords: Interval temporal logics, compass structures, decidability, complexity}
}
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