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New tool generates size-independent constraint models from data

Researchers have developed a Constraint Acquisition Tool capable of generating size-independent constraint programs from example solutions and input data. This tool identifies typical constraint patterns and generalizes them into models that can be applied to new datasets. The system outputs code in MiniZinc and provides a textual description of the generated model. Its effectiveness was demonstrated on problems from the PTHG21 Challenge, confirming the approach's viability. AI

IMPACT This research could improve the efficiency and applicability of constraint programming in various problem-solving domains.

RANK_REASON The cluster contains an academic paper describing a new method for constraint modeling. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New tool generates size-independent constraint models from data

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12 / 100
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The cluster contains an academic paper describing a new method for constraint modeling. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Helmut Simonis ·

    Learning Size Independent Constraint Models from Input Data and Positive and Negative Example Solutions

    arXiv:2610.13640v1 Announce Type: new Abstract: In this paper we describe a Constraint Acquisition Tool that generates size independent constraint programs from input data and positive and negative example solutions of multiple problem instances. The system finds size specific mo…