Representation Matters: Characterisation and Impossibility Results for Interval Aggregation
Authors: Ulle Endriss, Arianna Novaro, Zoi Terzopoulou
IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We show that on discrete scales it is essentially impossible to do so, while on continuous scales we can characterise the rules meeting these requirements as those that compute a weighted average of the endpoints of the individual intervals. Our main technical results show that (i) on discrete scales it is essentially impossible to design rules that are faithful to both representations (the only exceptions are so-called dictatorships), while (ii) on continuous scales a rule is faithful to both representations if and only if it is a weighted averaging rule. |
| Researcher Affiliation | Academia | 1Institute for Logic, Language and Computation (ILLC), University of Amsterdam 2Centre d Economie de la Sorbonne (CES), University of Paris 1 Panth eon-Sorbonne 3LAMSADE, Universit e Paris Dauphine-PSL |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and does not involve empirical studies with datasets for training or evaluation. |
| Dataset Splits | No | The paper is theoretical and does not involve empirical studies that would require dataset splits for validation. |
| Hardware Specification | No | The paper is theoretical and does not describe any experimental setup involving specific hardware. |
| Software Dependencies | No | The paper is theoretical and does not describe any experimental setup involving software dependencies with version numbers. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup with hyperparameters or configuration details. |