The Cube of Opposition: A Structure Underlying Many Knowledge Representation Formalisms
Authors: Didier Dubois, Henri Prade, Agnès Rico
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | After restating these results in a unified perspective, the paper proposes a graded extension of the cube and shows that several qualitative, as well as quantitative formalisms, such as Sugeno integrals used in multiple criteria aggregation and qualitative decision theory, or yet belief functions and Choquet integrals, are amenable to transformations that form graded cubes of opposition. |
| Researcher Affiliation | Academia | Didier Dubois1 and Henri Prade1,2 and Agn es Rico3 1. IRIT, CNRS & University of Toulouse, France 2. QCIS, University of Technology, Sydney, Australia 3. ERIC, Universit e Claude Bernard Lyon 1, 69100 Villeurbanne, France |
| Pseudocode | No | The information is insufficient as the paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper is theoretical and does not describe a methodology for which source code would be released. No mention of open-source code or repositories is found. |
| Open Datasets | No | The paper is theoretical and does not use datasets. No information about publicly available datasets is found. |
| Dataset Splits | No | The paper is theoretical and does not involve data splits for training, validation, or testing. |
| Hardware Specification | No | The paper is theoretical and does not describe computational experiments that would require specific hardware. No hardware specifications are mentioned. |
| Software Dependencies | No | The paper is theoretical and does not describe computational experiments that would require specific software dependencies with version numbers. No such details are mentioned. |
| Experiment Setup | No | The paper is theoretical and does not involve an experimental setup with hyperparameters or training configurations. |