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Documents authored by Belmecheri, Nassim


Artifact
Software
Peak-Utility Using CP

Authors: Chaima Hamdi, Nadjib Lazaar, Nassim Belmecheri, Djawad Bekkoucha, Said Jabbour, and Lakhdar Saïs


Abstract

Cite as

Chaima Hamdi, Nadjib Lazaar, Nassim Belmecheri, Djawad Bekkoucha, Said Jabbour, Lakhdar Saïs. Peak-Utility Using CP (Software). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@misc{dagstuhl-artifact-26906,
   title = {{Peak-Utility Using CP}}, 
   author = {Hamdi, Chaima and Lazaar, Nadjib and Belmecheri, Nassim and Bekkoucha, Djawad and Jabbour, Said and Sa\"{i}s, Lakhdar},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:0537fa0fd6f91dd5f7ed23d393bea3d15fa4d0fd;origin=https://gitlab.lisn.upsaclay.fr/dpm/peakutility;visit=swh:1:snp:2bf6143c24e9d95716a7f862397ac25c22afb6cb;anchor=swh:1:rev:9a5a4da55a1f9c6f61bd5df4ad5592675377d6a6}{\texttt{swh:1:dir:0537fa0fd6f91dd5f7ed23d393bea3d15fa4d0fd}} (visited on 2026-07-13)},
   url = {https://gitlab.lisn.upsaclay.fr/dpm/peakutility.git},
   doi = {10.4230/artifacts.26906},
}
Document
ScenaGen: A CP Model for Grounding Qualitative Driving Scenarios

Authors: Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar, and Helge Spieker

Published in: LIPIcs, Volume 379, 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)


Abstract
Validating Automated Driving Systems (ADS) requires generating various kinematically executable traffic scenarios. The grounding of qualitative descriptions into concrete trajectories is a combinatorial task poorly addressed by learning-based methods. We propose ScenaGen, a CP model operating on qualitative explainable graphs (QXGs) to encode spatio-temporal relations between traffic entities. Formulated over integer position variables, ScenaGen enforces qualitative spatial constraints, distance thresholds, and inter-frame kinematic consistency. A single QXG acts as a formal template for systematically enumerating distinct, quantitatively varied concrete scenarios. Evaluation of synthetic and real-world benchmarks demonstrates that ScenaGen provides a robust and efficient alternative for scenario instantiation, outperforming standard search baselines in both scalability and solution diversity.

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Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar, and Helge Spieker. ScenaGen: A CP Model for Grounding Qualitative Driving Scenarios. In 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 379, pp. 4:1-4:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{belmecheri_et_al:LIPIcs.CP.2026.4,
  author =	{Belmecheri, Nassim and Gotlieb, Arnaud and Lazaar, Nadjib and Spieker, Helge},
  title =	{{ScenaGen: A CP Model for Grounding Qualitative Driving Scenarios}},
  booktitle =	{32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)},
  pages =	{4:1--4:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-432-1},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{379},
  editor =	{Beldiceanu, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2026.4},
  URN =		{urn:nbn:de:0030-drops-266378},
  doi =		{10.4230/LIPIcs.CP.2026.4},
  annote =	{Keywords: Constraint Programming, Scenario Grounding, Qualitative Reasoning, Autonomous Driving, Application}
}
Document
Utility-Peak Itemset Mining with Constraint Programming

Authors: Chaima Hamdi, Nadjib Lazaar, Nassim Belmecheri, Djawad Bekkoucha, Said Jabbour, and Lakhdar Saïs

Published in: LIPIcs, Volume 379, 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)


Abstract
High-Utility Itemset Mining (HUIM) aims to discover itemsets whose utility exceeds a given threshold. While specialized algorithms achieve strong performance, they lack flexibility when additional domain constraints must be incorporated. Constraint Programming (CP) offers a declarative alternative, but requires strong propagation to remain competitive. In this paper, we propose a CP framework for utility-driven pattern mining based on a parameterized global constraint that unifies the enumeration of High-Utility Itemsets (HUIs) and a new condensed representation called Utility-Peak Itemsets (UPIs). A UPI is an itemset whose utility is greater or equal than that of all its immediate subsets and supersets, capturing locally utility-maximal patterns. We study the computational complexity of UPI mining and show that deciding whether a high-utility UPI exists, for a given utility threshold, is NP-complete. Our global constraint, PeakUtility, integrates utility computation and upper-bound pruning through propagation rules. Experiments demonstrate that our approach performs competitively with the state of the art HUIM algorithms while preserving the modelling flexibility of CP.

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Chaima Hamdi, Nadjib Lazaar, Nassim Belmecheri, Djawad Bekkoucha, Said Jabbour, and Lakhdar Saïs. Utility-Peak Itemset Mining with Constraint Programming. In 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 379, pp. 27:1-27:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{hamdi_et_al:LIPIcs.CP.2026.27,
  author =	{Hamdi, Chaima and Lazaar, Nadjib and Belmecheri, Nassim and Bekkoucha, Djawad and Jabbour, Said and Sa\"{i}s, Lakhdar},
  title =	{{Utility-Peak Itemset Mining with Constraint Programming}},
  booktitle =	{32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)},
  pages =	{27:1--27:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-432-1},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{379},
  editor =	{Beldiceanu, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2026.27},
  URN =		{urn:nbn:de:0030-drops-266595},
  doi =		{10.4230/LIPIcs.CP.2026.27},
  annote =	{Keywords: Constraint Programming, Pattern Mining, HUI Mining, Global Constraints, Declarative Data Mining}
}
Artifact
Software
QualiNet

Authors: Nassim Belmecheri


Abstract

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Nassim Belmecheri. QualiNet (Software, Source code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@misc{dagstuhl-artifact-24755,
   title = {{QualiNet}}, 
   author = {Belmecheri, Nassim},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:a4900663aeb84632699b0217f7a7f98014466c00;origin=https://github.com/nassimbel/QualiNet;visit=swh:1:snp:425d9e3015b7c13a2d10dfb966d88146d85121d7;anchor=swh:1:rev:95ded8256592cacf31eeca422dd61aa8515f74ad}{\texttt{swh:1:dir:a4900663aeb84632699b0217f7a7f98014466c00}} (visited on 2025-10-13)},
   url = {https://github.com/nassimbel/QualiNet.git},
   doi = {10.4230/artifacts.24755},
}
Document
Short Paper
QualiNet: Acquiring Bird’s Eye View Qualitative Spatial Representation from 2D Images in Automated Vehicle Perception (Short Paper)

Authors: Nassim Belmecheri

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


Abstract
We present QualiNet, an end-to-end deep learning framework that acquires Bird’s Eye View (BEV) qualitative spatial relations directly from 2D images, eliminating the need for depth sensors. The system combines 2D object detection, masking, and classification to infer Rectangle Algebra (RA) and Qualitative Distance Calculus (QDC) relations. Evaluated on NuScenes and PandaSet datasets, QualiNet achieves 91% accuracy for RA, 80% for QDC, and 99% top-2 accuracy, demonstrating robust performance for automated vehicle perception.

Cite as

Nassim Belmecheri. QualiNet: Acquiring Bird’s Eye View Qualitative Spatial Representation from 2D Images in Automated Vehicle Perception (Short Paper). In 32nd International Symposium on Temporal Representation and Reasoning (TIME 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 355, pp. 14:1-14:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{belmecheri:LIPIcs.TIME.2025.14,
  author =	{Belmecheri, Nassim},
  title =	{{QualiNet: Acquiring Bird’s Eye View Qualitative Spatial Representation from 2D Images in Automated Vehicle Perception}},
  booktitle =	{32nd International Symposium on Temporal Representation and Reasoning (TIME 2025)},
  pages =	{14:1--14:6},
  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.2025.14},
  URN =		{urn:nbn:de:0030-drops-244608},
  doi =		{10.4230/LIPIcs.TIME.2025.14},
  annote =	{Keywords: Qualitative Spatial Representation, Deep Learning, Computer vision, Qualitative Scene Understanding, Spatio-temporal representation and reasoning models (including moving objects tracking)}
}
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