Multiple Constraint Acquisition

Authors: Robin Arcangioli, Christian Bessiere, Nadjib Lazaar

IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental We made experiments to evaluate the performance of MULTIACQ and its find All Scopes function compared to QUACQ. We also evaluate the version using cut-offs, that we call MACQ-CO (i.e., MULTIAcq with Cuts-Offs).
Researcher Affiliation Academia Robin Arcangioli, Christian Bessiere, Nadjib Lazaar CNRS, University of Montpellier, France
Pseudocode Yes Algorithme 1 : MULTIACQ
Open Source Code No The paper does not provide explicit access to its source code (e.g., a repository link or a statement about code release in supplementary materials).
Open Datasets Yes CSPLib : a benchmark library for constraints. http://www.csplib.org/, 1999.
Dataset Splits No The paper describes an active learning process where the system interactively queries the user for examples. It does not define traditional train/validation/test splits for datasets, as examples are generated and classified on the fly during the acquisition process.
Hardware Specification Yes Our tests were conducted on an 1,6 GHz Intel Core i5 with 4.0GB of RAM (1600 MHz DDR3).
Software Dependencies No The paper mentions the names of systems like QUACQ, MULTIACQ, and MACQ-CO, and concepts like constraint programming and SAT, but it does not specify any particular software dependencies with version numbers (e.g., specific libraries, compilers, or operating systems).
Experiment Setup Yes The cutoff on the time between two queries has been set to 5 seconds. This is an acceptable waiting time for a human user. We combine the cutoff technique with a second heuristic based on reordering the variables.