3 Search Results for "Taupe, Richard"

Document
Invited Paper
DOI: 10.4230/OASIcs.RW.2024/2025.8
ASP Essentials: Modelling and Efficient Solving (Invited Paper)

Authors: Giuseppe Mazzotta and Francesco Ricca

Published in: OASIcs, Volume 138, Joint Proceedings of the 20th and 21st Reasoning Web Summer Schools (RW 2024 & RW 2025)

Abstract
Answer Set Programming (ASP) is a logic-based Knowledge Representation and Reasoning (KRR) paradigm that facilitates rapid prototyping of solutions for complex problems. It is particularly effective for tackling Deep Reasoning tasks involving exponentially large search spaces, such as combinatorial search and optimization. While getting started with ASP is relatively easy, mastering its advanced constructs and scaling solutions to real-world problem sizes can be challenging. This paper provides an introduction to ASP, guiding the reader from the fundamentals of the language to the application of programming methodologies and the computation of answer sets. Beyond the core framework, the paper also examines selected extensions of ASP that enable the modeling of complex problems, as well as compilation techniques designed to enhance solving efficiency. Furthermore, it mentions some recent tools that combine ASP with LLMs.
Cite as

Giuseppe Mazzotta and Francesco Ricca. ASP Essentials: Modelling and Efficient Solving (Invited Paper). In Joint Proceedings of the 20th and 21st Reasoning Web Summer Schools (RW 2024 & RW 2025). Open Access Series in Informatics (OASIcs), Volume 138, pp. 8:1-8:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{mazzotta_et_al:OASIcs.RW.2024/2025.8,
  author =	{Mazzotta, Giuseppe and Ricca, Francesco},
  title =	{{ASP Essentials: Modelling and Efficient Solving}},
  booktitle =	{Joint Proceedings of the 20th and 21st Reasoning Web Summer Schools (RW 2024 \& RW 2025)},
  pages =	{8:1--8:21},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-405-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{138},
  editor =	{Artale, Alessandro and Bienvenu, Meghyn and Garc{\'\i}a, Yazm{\'\i}n Ib\'{a}\~{n}ez and Murlak, Filip},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.RW.2024/2025.8},
  URN =		{urn:nbn:de:0030-drops-250539},
  doi =		{10.4230/OASIcs.RW.2024/2025.8},
  annote =	{Keywords: Answer Set Programming, ASP with Quantifiers, Grounding Bottleneck, Compilation-based ASP solving, Neurosymbolic AI, LLMs}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.7
Optimizing 2D Cutting: A Bin Packing Approach to Minimize Scraps and Maximize Their Reusability

Authors: Manuel Chastenay, Xavier Zwingmann, Claude-Guy Quimper, and Jonathan Gaudreault

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
In industrial settings, cutting predefined pieces from one or multiple sheets of material is a common optimization challenge. This problem can be formulated as a variant of the 2D bin packing problem, where the edges of the pieces define the cut lines. This paper presents a constraint programming model developed in collaboration with an industrial partner in construction to minimize scrap waste generated when cutting insulation pieces. The model introduces an objective function designed to maximize the reusability of leftover material. To fully leverage the model’s efficiency, an initial process transforms irregular insulation pieces into rectangles using one of four processing methods. A comparative analysis is conducted to evaluate the impact of these methods, as well as to benchmark the model’s results against the partner’s manual approach.
Cite as

Manuel Chastenay, Xavier Zwingmann, Claude-Guy Quimper, and Jonathan Gaudreault. Optimizing 2D Cutting: A Bin Packing Approach to Minimize Scraps and Maximize Their Reusability. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 7:1-7:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{chastenay_et_al:LIPIcs.CP.2025.7,
  author =	{Chastenay, Manuel and Zwingmann, Xavier and Quimper, Claude-Guy and Gaudreault, Jonathan},
  title =	{{Optimizing 2D Cutting: A Bin Packing Approach to Minimize Scraps and Maximize Their Reusability}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{7:1--7:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.7},
  URN =		{urn:nbn:de:0030-drops-238685},
  doi =		{10.4230/LIPIcs.CP.2025.7},
  annote =	{Keywords: Combinatorial optimization, constraint programming, 2D bin packing}
}
Document
DOI: 10.4230/OASIcs.ICLP.2018.20
Speeding up Lazy-Grounding Answer Set Solving

Authors: Richard Taupe

Published in: OASIcs, Volume 64, Technical Communications of the 34th International Conference on Logic Programming (ICLP 2018)

Abstract
The grounding bottleneck is an important open issue in Answer Set Programming. Lazy grounding addresses it by interleaving grounding and search. The performance of current lazy-grounding solvers is not yet comparable to that of ground-and-solve systems, however. The aim of this thesis is to extend prior work on lazy grounding by novel heuristics and other techniques like non-ground conflict learning in order to speed up solving. Parts of expected results will be beneficial for ground-and-solve systems as well.
Cite as

Richard Taupe. Speeding up Lazy-Grounding Answer Set Solving. In Technical Communications of the 34th International Conference on Logic Programming (ICLP 2018). Open Access Series in Informatics (OASIcs), Volume 64, pp. 20:1-20:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{taupe:OASIcs.ICLP.2018.20,
  author =	{Taupe, Richard},
  title =	{{Speeding up Lazy-Grounding Answer Set Solving}},
  booktitle =	{Technical Communications of the 34th International Conference on Logic Programming (ICLP 2018)},
  pages =	{20:1--20:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-090-3},
  ISSN =	{2190-6807},
  year =	{2018},
  volume =	{64},
  editor =	{Dal Palu', Alessandro and Tarau, Paul and Saeedloei, Neda and Fodor, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICLP.2018.20},
  URN =		{urn:nbn:de:0030-drops-98861},
  doi =		{10.4230/OASIcs.ICLP.2018.20},
  annote =	{Keywords: answer set programming, lazy grounding, heuristics}
}
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