Constraint acquisition needs better benchmarks

Computer Science > Artificial Intelligence [Submitted on 25 May 2026] Constraint acquisition needs better benchmarks Rafał Stachowiak, Tomasz P. Pawlak Constraint Acquisition (CA) and related research on the validation and enhancement of Mathematical Programming (MP) models from domain knowledge artifacts are currently limited by inadequate benchmarks. This deficiency impedes reproducibility and cross-study comparability, slowing the maturation of CA methods. Existing benchmarks were designed for solver evaluation rather than for assessing CA algorithms. They are loosely organized, treat individual problems inconsistently, and omit the domain knowledge artifacts required by CA methods. This work presents MPMMine, a benchmark suite designed to assess algorithms that discover, validate, and enhance MP models using diverse domain knowledge artifacts. MPMMine is guided by consistency, standardization, completeness, extensibility, openness, and version control. It adopts a uniform structure and relies on open formats: MiniZinc, CommonMark, and JSON. It provides multiple models per problem, tens of instances per model, and thousands of solutions and non-solutions in both integer and continuous domains, alongside natural-language descriptions to support text-to-model methods. Comments: 12 pages, 1 figure, for the associated dataset, see this https URL Subjects: Artificial Intelligence (cs.AI); Computational Engineering, Finance, and Science (cs.CE) MSC classes: 90C90 (Primary), 90C05 (Secondary) ACM classes: I.6.3; I.2.2; I.2.7 Cite as: arXiv:2605.26279 [cs.AI]   (or arXiv:2605.26279v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2605.26279 Focus to learn more Submission history From: Tomasz Pawlak [view email] [v1] Mon, 25 May 2026 19:05:12 UTC (801 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-05 Change to browse by: cs cs.CE References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)