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..
Encoding Multi-Valued Decision Diagram Constraints as Binary Constraint Trees
Authors: Ruiwei Wang, Roland H.C. Yap3850-3858
AAAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experimental results on a large set of benchmarks show that the BCT GAC algorithm can significantly outperform state-of-the-art MDD as well as table GAC algorithms. ... Experiments We evaluate the effectiveness of the reduction rules (compression ratio) and efficiency of GAC algorithms in the Abscon solver. |
| Researcher Affiliation | Academia | Ruiwei Wang and Roland H.C. Yap School of Computing, National University of Singapore, 13 Computing Drive, 117417, Singapore EMAIL |
| Pseudocode | Yes | Algorithm 1: Reducing DTBE(c ) ... Algorithm 2: revise(c, x) |
| Open Source Code | No | The paper mentions the Abscon solver (https://www.cril.univ-artois.fr/%7Elecoutre/#/softwares) which is a third-party tool used for experiments, but it does not provide any statement or link for the open-source code of their proposed methodology (BCT, TBE, or reduction rules). |
| Open Datasets | Yes | Car Sequencing: we use 30 Caroline Gagne hard instances (denoted as C-1) from CSPlib.4 ... Pentominoes: we use 5 instances (denoted as P-m) from Minizinc Challenge 2020 and 36 instances from the pentominoes generator website.5 ... Nurse Scheduling: we use the model 1 and 2, denoted as N-1 and N-2, from (Gange, Stuckey, and Szymanek 2011)... XCSP: we use all 2559 non-binary instances which only employ table constraints from the XCSP website7 |
| Dataset Splits | No | The paper describes evaluation on benchmark instances, but it does not specify any training/test/validation dataset splits. The experimental setup focuses on solving pre-existing instances within time/memory limits rather than model training and validation splits. |
| Hardware Specification | Yes | Experiments were run on a 3.20GHz Intel i7-8700 machine. |
| Software Dependencies | No | The paper mentions using the 'Abscon solver' and indicates it is implemented in 'Abscon solver' (https://www.cril.univ-artois.fr/%7Elecoutre/#/softwares), but it does not provide specific version numbers for the Abscon solver or any other software libraries or dependencies used in their experiments. |
| Experiment Setup | Yes | The variable and value search heuristics used are Activity (Michel and Van Hentenryck 2012) and lexical value order. The initial cutoff = 10 and ρ = 1.1. For each restart, cutoff is the allowed number of failed assignments and cutoff increases by (cutoff ρ) after restart. |