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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
A BTP-Based Family of Variable Elimination Rules for Binary CSPs
Authors: Achref El Mouelhi3871
AAAI 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The main contribution of this work is providing a new weaker-form of BTP, called m-f BTP, which allows variable elimination and deο¬nes a new tractable class for which arc consistency is a decision procedure. The results proven in this paper also provide theoretical insight into the relationship between m-f BTP and some others previous extension of BTP such as k-BTP, m-w BTP, WBTP (Naanaa 2016). |
| Researcher Affiliation | Academia | Achref El Mouelhi Aix Marseille Univ, Universit e de Toulon CNRS, ENSAM, LSIS Marseille, France EMAIL |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any explicit statements or links regarding open-source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not describe experiments involving datasets, thus no information on public dataset access is provided. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical validation or dataset splits. |
| Hardware Specification | No | The paper is theoretical and does not describe any experiments that would require hardware specifications. |
| Software Dependencies | No | The paper is theoretical and does not describe any experiments that would require specific software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup, hyperparameters, or training settings. |