8 Search Results for "Wallace, Mark"

Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2024.26
Comparisons of Chicago Neighborhood Boundaries from Crowdsourced Resident Drawings (Short Paper)

Authors: Crystal J. Bae, Lydia Wileden, and Emily Talen

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
The idea of the urban neighborhood has long been of interest to residents, planners, and scholars. We describe a project focused on Chicago neighborhood mapping and pose related questions about the analysis of crowdsourced neighborhood boundary drawings. To gain insight into Chicago residents’ cognitive maps and the relationship between those internal representations and existing administrative boundaries, the authors launched the Chicago Neighborhood Project (CNP), which invited Chicago residents to draw their own and other neighborhoods within the city using an online mapping interface. The goal of CNP is to examine variation in how neighborhoods are defined by residents and use that variation to inform how policymakers, planners, and researchers create, implement, and measure place-based policies. Because the project had a goal of collecting a large sample of neighborhood map drawings, the project took a crowdsourced approach, recruiting responses via email to community groups, social media, targeted web advertisements, flyering, collaborations with news media, and word of mouth. This paper describes our data collection methodology, resulting in over 5,000 responses, as well as decisions related to initial data cleaning and analysis. We present early findings from the project in relation to understanding Chicago residents' cognitive boundaries of the "neighborhood." TL;DR: We present preliminary results of the Chicago Neighborhood Project (CNP), which collected over 5,000 drawings of neighborhood areas from residents, making it the largest such effort to elicit an understanding of neighborhood regions in Chicago.
Cite as

Crystal J. Bae, Lydia Wileden, and Emily Talen. Comparisons of Chicago Neighborhood Boundaries from Crowdsourced Resident Drawings (Short Paper). In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 26:1-26:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{bae_et_al:LIPIcs.COSIT.2024.26,
  author =	{Bae, Crystal J. and Wileden, Lydia and Talen, Emily},
  title =	{{Comparisons of Chicago Neighborhood Boundaries from Crowdsourced Resident Drawings}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{26:1--26:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.26},
  URN =		{urn:nbn:de:0030-drops-208419},
  doi =		{10.4230/LIPIcs.COSIT.2024.26},
  annote =	{Keywords: cognitive regions, urban neighborhoods, boundary mapping, sketch mapping}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2024.31
Large Language Models: Testing Their Capabilities to Understand and Explain Spatial Concepts (Short Paper)

Authors: Majid Hojati and Rob Feick

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
Interest in applying Large Language Models (LLMs), which use natural language processing (NLP) to provide human-like responses to text-based questions, to geospatial tasks has grown rapidly. Research shows that LLMs can help generate software code and answer some types of geographic questions to varying degrees even without fine-tuning. However, further research is required to explore the types of spatial questions they answer correctly, their abilities to apply spatial reasoning, and the variability between models. In this paper we examine the ability of four LLM models (GPT3.5 and 4, LLAma2.0, Falcon40B) to answer spatial questions that range from basic calculations to more advanced geographic concepts. The intent of this comparison is twofold. First, we demonstrate an extensible method for evaluating LLM’s limitations to supporting spatial data science through correct calculations and code generation. Relatedly, we also consider how these models can aid geospatial learning by providing text-based explanations of spatial concepts and operations. Our research shows common strengths in more basic types of questions, and mixed results for questions relating to more advanced spatial concepts. These results provide insights that may be used to inform strategies for testing and fine-tuning these models to increase their understanding of key spatial concepts.
Cite as

Majid Hojati and Rob Feick. Large Language Models: Testing Their Capabilities to Understand and Explain Spatial Concepts (Short Paper). In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 31:1-31:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{hojati_et_al:LIPIcs.COSIT.2024.31,
  author =	{Hojati, Majid and Feick, Rob},
  title =	{{Large Language Models: Testing Their Capabilities to Understand and Explain Spatial Concepts}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{31:1--31:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.31},
  URN =		{urn:nbn:de:0030-drops-208460},
  doi =		{10.4230/LIPIcs.COSIT.2024.31},
  annote =	{Keywords: Geospatial concepts, Large Language Models, LLM, GPT, Llama, Falcon}
}
Document
DOI: 10.4230/LIPIcs.CP.2024.7
Cumulative Scheduling with Calendars and Overtime

Authors: Samuel Cloutier and Claude-Guy Quimper

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
In project scheduling, calendar considerations can increase the duration of a task when its execution overlaps with holidays. On the other hand, the use of overtime may decrease the task’s duration. We introduce the CalendarOvertime constraint which verifies that a task follows a calendar with overtime and holidays. We also introduce the CumulativeOvertime constraint, a variant of the Cumulative constraint, that also reasons with the calendars when propagating according to the resource consumption, the overtime, and the holidays. Experimental results of a RCPSP model on the PSPLIB, BL, and PACK instances augmented with calendars and overtime show that the use of the CalendarOvertime constraint offers a speedup greater than 2.9 on the instances optimally solved and finds better solutions on more than 79% of the remaining instances when compared to a decomposition of the constraint. We also show that the use of our CumulativeOvertime constraint further improves these results.
Cite as

Samuel Cloutier and Claude-Guy Quimper. Cumulative Scheduling with Calendars and Overtime. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 7:1-7:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{cloutier_et_al:LIPIcs.CP.2024.7,
  author =	{Cloutier, Samuel and Quimper, Claude-Guy},
  title =	{{Cumulative Scheduling with Calendars and Overtime}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{7:1--7:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.7},
  URN =		{urn:nbn:de:0030-drops-206927},
  doi =		{10.4230/LIPIcs.CP.2024.7},
  annote =	{Keywords: Constraint programming, Scheduling, Global constraints, Calendars, Overtime, Cumulative constraint, Time-Tabling}
}
Document
DOI: 10.4230/LIPIcs.CP.2024.17
Exponential Steepest Ascent from Valued Constraint Graphs of Pathwidth Four

Authors: Artem Kaznatcheev and Melle van Marle

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
We examine the complexity of maximising fitness via local search on valued constraint satisfaction problems (VCSPs). We consider two kinds of local ascents: (1) steepest ascents, where each step changes the domain that produces a maximal increase in fitness; and (2) ≺-ordered ascents, where - of the domains with available fitness increasing changes - each step changes the ≺-minimal domain. We provide a general padding argument to simulate any ordered ascent by a steepest ascent. We construct a VCSP that is a path of binary constraints between alternating 2-state and 3-state domains with exponentially long ordered ascents. We apply our padding argument to this VCSP to obtain a Boolean VCSP that has a constraint (hyper)graph of arity 5 and pathwidth 4 with exponential steepest ascents. This is an improvement on the previous best known construction for long steepest ascents, which had arity 8 and pathwidth 7.
Cite as

Artem Kaznatcheev and Melle van Marle. Exponential Steepest Ascent from Valued Constraint Graphs of Pathwidth Four. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 17:1-17:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{kaznatcheev_et_al:LIPIcs.CP.2024.17,
  author =	{Kaznatcheev, Artem and van Marle, Melle},
  title =	{{Exponential Steepest Ascent from Valued Constraint Graphs of Pathwidth Four}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{17:1--17:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.17},
  URN =		{urn:nbn:de:0030-drops-207021},
  doi =		{10.4230/LIPIcs.CP.2024.17},
  annote =	{Keywords: valued constraint satisfaction problem, steepest ascent, local search, bounded treewidth, intractability}
}
Document
DOI: 10.4230/LIPIcs.CP.2024.20
Constraint Modelling with LLMs Using In-Context Learning

Authors: Kostis Michailidis, Dimos Tsouros, and Tias Guns

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
Constraint Programming (CP) allows for the modelling and solving of a wide range of combinatorial problems. However, modelling such problems using constraints over decision variables still requires significant expertise, both in conceptual thinking and syntactic use of modelling languages. In this work, we explore the potential of using pre-trained Large Language Models (LLMs) as coding assistants, to transform textual problem descriptions into concrete and executable CP specifications. We present different transformation pipelines with explicit intermediate representations, and we investigate the potential benefit of various retrieval-augmented example selection strategies for in-context learning. We evaluate our approach on 2 datasets from the literature, namely NL4Opt (optimisation) and Logic Grid Puzzles (satisfaction), and a heterogeneous set of exercises from a CP course. The results show that pre-trained LLMs have promising potential for initialising the modelling process, with retrieval-augmented in-context learning significantly enhancing their modelling capabilities.
Cite as

Kostis Michailidis, Dimos Tsouros, and Tias Guns. Constraint Modelling with LLMs Using In-Context Learning. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 20:1-20:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{michailidis_et_al:LIPIcs.CP.2024.20,
  author =	{Michailidis, Kostis and Tsouros, Dimos and Guns, Tias},
  title =	{{Constraint Modelling with LLMs Using In-Context Learning}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{20:1--20:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.20},
  URN =		{urn:nbn:de:0030-drops-207053},
  doi =		{10.4230/LIPIcs.CP.2024.20},
  annote =	{Keywords: Constraint Modelling, Constraint Acquisition, Constraint Programming, Large Language Models, In-Context Learning, Natural Language Processing, Named Entity Recognition, Retrieval-Augmented Generation, Optimisation}
}
Document
DOI: 10.4230/LIPIcs.CP.2024.29
Mutational Fuzz Testing for Constraint Modeling Systems

Authors: Wout Vanroose, Ignace Bleukx, Jo Devriendt, Dimos Tsouros, Hélène Verhaeghe, and Tias Guns

Published in: LIPIcs, Volume 307, 30th International Conference on Principles and Practice of Constraint Programming (CP 2024)

Abstract
Constraint programming (CP) modeling languages, like MiniZinc, Essence and CPMpy, play a crucial role in making CP technology accessible to non-experts. Both solver-independent modeling frameworks and solvers themselves are complex pieces of software that can contain bugs, which undermines their usefulness. Mutational fuzz testing is a way to test complex systems by stochastically mutating input and verifying preserved properties of the mutated output. We investigate different mutations and verification methods that can be used on the constraint specifications directly. This includes methods proposed in the context of SMT problem specifications, as well as new methods related to global constraints, optimization, and solution counting/preservation. Our results show that such a fuzz testing approach improves the overall code coverage of a modeling system compared to only unit testing, and is able to find bugs in the whole toolchain, from the modeling language transformations themselves to the underlying solvers.
Cite as

Wout Vanroose, Ignace Bleukx, Jo Devriendt, Dimos Tsouros, Hélène Verhaeghe, and Tias Guns. Mutational Fuzz Testing for Constraint Modeling Systems. In 30th International Conference on Principles and Practice of Constraint Programming (CP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 307, pp. 29:1-29:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{vanroose_et_al:LIPIcs.CP.2024.29,
  author =	{Vanroose, Wout and Bleukx, Ignace and Devriendt, Jo and Tsouros, Dimos and Verhaeghe, H\'{e}l\`{e}ne and Guns, Tias},
  title =	{{Mutational Fuzz Testing for Constraint Modeling Systems}},
  booktitle =	{30th International Conference on Principles and Practice of Constraint Programming (CP 2024)},
  pages =	{29:1--29:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-336-2},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{307},
  editor =	{Shaw, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2024.29},
  URN =		{urn:nbn:de:0030-drops-207149},
  doi =		{10.4230/LIPIcs.CP.2024.29},
  annote =	{Keywords: fuzz testing, Constraint modeling language, bugs, mutational testing, modeling, constraint reformulation}
}
Document
DOI: 10.4230/LIPIcs.CP.2021.49
Human-Centred Feasibility Restoration

Authors: Ilankaikone Senthooran, Matthias Klapperstueck, Gleb Belov, Tobias Czauderna, Kevin Leo, Mark Wallace, Michael Wybrow, and Maria Garcia de la Banda

Published in: LIPIcs, Volume 210, 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)

Abstract
Decision systems for solving real-world combinatorial problems must be able to report infeasibility in such a way that users can understand the reasons behind it, and understand how to modify the problem to restore feasibility. Current methods mainly focus on reporting one or more subsets of the problem constraints that cause infeasibility. Methods that also show users how to restore feasibility tend to be less flexible and/or problem-dependent. We describe a problem-independent approach to feasibility restoration that combines existing techniques from the literature in novel ways to yield meaningful, useful, practical and flexible user support. We evaluate the resulting framework on two real-world applications.
Cite as

Ilankaikone Senthooran, Matthias Klapperstueck, Gleb Belov, Tobias Czauderna, Kevin Leo, Mark Wallace, Michael Wybrow, and Maria Garcia de la Banda. Human-Centred Feasibility Restoration. In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 49:1-49:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{senthooran_et_al:LIPIcs.CP.2021.49,
  author =	{Senthooran, Ilankaikone and Klapperstueck, Matthias and Belov, Gleb and Czauderna, Tobias and Leo, Kevin and Wallace, Mark and Wybrow, Michael and de la Banda, Maria Garcia},
  title =	{{Human-Centred Feasibility Restoration}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{49:1--49:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2021.49},
  URN =		{urn:nbn:de:0030-drops-153408},
  doi =		{10.4230/LIPIcs.CP.2021.49},
  annote =	{Keywords: Combinatorial optimisation, modelling, human-centred, conflict resolution, feasibility restoration, explainable AI, soft constraints}
}
Document
DOI: 10.4230/DagSemProc.09261.6
Branch-and-Price Solving in G12

Authors: Jakob Puchinger, Peter Stuckey, Mark Wallace, and Sebastian Brand

Published in: Dagstuhl Seminar Proceedings, Volume 9261, Models and Algorithms for Optimization in Logistics (2009)

Abstract
The G12 project is developing a software environment for stating and solving combinatorial problems by mapping a high-level model of the problem to an efficient combination of solving methods. Model annotations are used to control this process. In this paper we explain the mapping to branch-and-price solving. G12 supports the selection of specialised subproblem solvers, the aggregation of identical subproblems, automatic disaggregation when required by search, and the use of specialised branching rules. We demonstrate the benefits of the G12 framework on three examples: a trucking problem, cutting stock, and two-dimensional bin packing.
Cite as

Jakob Puchinger, Peter Stuckey, Mark Wallace, and Sebastian Brand. Branch-and-Price Solving in G12. In Models and Algorithms for Optimization in Logistics. Dagstuhl Seminar Proceedings, Volume 9261, pp. 1-3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{puchinger_et_al:DagSemProc.09261.6,
  author =	{Puchinger, Jakob and Stuckey, Peter and Wallace, Mark and Brand, Sebastian},
  title =	{{Branch-and-Price Solving in G12}},
  booktitle =	{Models and Algorithms for Optimization in Logistics},
  pages =	{1--3},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9261},
  editor =	{Cynthia Barnhart and Uwe Clausen and Ulrich Lauther and Rolf H. M\"{o}hring},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09261.6},
  URN =		{urn:nbn:de:0030-drops-21641},
  doi =		{10.4230/DagSemProc.09261.6},
  annote =	{Keywords: Combinatorial optimization, branch-and-price, software}
}
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