Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
A Reactive Strategy for High-Level Consistency During Search
Authors: Robert J. Woodward, Berthe Y. Choueiry, Christian Bessiere
IJCAI 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We validate our approach on benchmark problems using Partition-One Arc Consistency as an HLC. However, our strategy is generic and can be used with other higher-level consistency algorithms. |
| Researcher Affiliation | Academia | Robert J. Woodward,1,2 Berthe Y. Choueiry,1 Christian Bessiere,2 1 Constraint Systems Laboratory, University of Nebraska-Lincoln, USA 2 CNRS, University of Montpellier, France EMAIL, EMAIL, EMAIL |
| Pseudocode | Yes | Algorithm 1: UNLABEL(i,consistent) unlabels variable xi |
| Open Source Code | No | No explicit statement about providing open-source code for the methodology described in the paper. |
| Open Datasets | Yes | We use the benchmark problems available from Lecoutre s website.3 www.cril.univ-artois.fr/ lecoutre/benchmarks.html |
| Dataset Splits | No | We use the benchmark problems available from Lecoutre s website.3 www.cril.univ-artois.fr/ lecoutre/benchmarks.html |
| Hardware Specification | No | This work was completed utilizing the Holland Computing Center of the University of Nebraska, which receives support from the Nebraska Research Initiative. |
| Software Dependencies | No | No specific software dependencies with version numbers (e.g., library names, programming language versions, or solver versions) are mentioned. |
| Experiment Setup | Yes | We use a time limit of 60 minutes per instance and 8GB of memory. |