Quantification of Resource Production Incompleteness
Authors: Yakoub Salhi6480-6487
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we introduce a logic-based framework for measuring resource production incompleteness: the greater the value returned by a measure, the greater is the intensity of incompleteness. |
| Researcher Affiliation | Academia | Yakoub Salhi CRIL, U. Artois & CNRS, Lens, France salhi@cril.fr |
| Pseudocode | No | The paper describes logical rules and definitions (e.g., Sequent Calculus CIMAAL in Figure 1), but it does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper is theoretical and focuses on a logic-based framework; there is no mention of releasing open-source code for any implementation. |
| Open Datasets | No | The paper is theoretical and introduces a logic-based framework; it does not use datasets for training. |
| Dataset Splits | No | The paper is theoretical and does not involve experimental validation on datasets, thus no dataset split information is provided. |
| Hardware Specification | No | The paper is theoretical and introduces a logic-based framework; it does not report on computational experiments, and therefore no hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not involve software implementation or computational experiments, therefore no software dependencies with version numbers are mentioned. |
| Experiment Setup | No | The paper is theoretical, focusing on a logic-based framework; it does not detail any experimental setup, hyperparameters, or training configurations. |