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..
Explaining Multi-Criteria Decision Aiding Models with an Extended Shapley Value
Authors: Christophe Labreuche, Simon Fossier
IJCAI 2018 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We randomly generated trees having at most 100 criteria, at most 6 children at each level and maximal depth of 5. We also randomly generated options x, y and 2-additive Choquet integrals for U. For each instance, we store the average time to compute one index IEOw i (average over i NT ). Table 1 shows the computation times over 25 000 generations performed on a computer equipped with 3.1 GHz Intel Core i7. |
| Researcher Affiliation | Industry | Christophe Labreuche, Simon Fossier Thales Research & Technology, 1 avenue Fresnel, 91767 Palaiseau cedex, France EMAIL |
| Pseudocode | No | The paper provides mathematical derivations and examples, but does not include any clearly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any explicit statement about making its source code publicly available or providing a link to a code repository. |
| Open Datasets | No | The paper uses 'randomly generated trees' and 'randomly generated options x, y' for its computational analysis, and a 'running example' for illustration, but does not use or provide access information for a publicly available or open dataset. |
| Dataset Splits | No | The paper does not specify any dataset splits (train/validation/test) as it uses randomly generated data and illustrative examples rather than fixed datasets. |
| Hardware Specification | Yes | Table 1 shows the computation times over 25 000 generations performed on a computer equipped with 3.1 GHz Intel Core i7. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers (e.g., 'Python 3.8', 'PyTorch 1.9'). |
| Experiment Setup | Yes | We randomly generated trees having at most 100 criteria, at most 6 children at each level and maximal depth of 5. We also randomly generated options x, y and 2-additive Choquet integrals for U. |