On Middle Grounds for Preference Statements
Authors: Anne-Marie George, Ana Ozaki
IJCAI 2025 | Venue PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We prove theoretical results on the existence and uniqueness of middle grounds. In particular, we show that, for preference statements, middle grounds may not exist and may not be unique. We also provide algorithms for deciding the existence and finding middle grounds. This paper contributes with the following theoretical results. General Notion of Middle Ground (MG): We provide a general definition of middle ground for satisfaction systems (Section 3.1), show conditions for existence of a MG (Section 3.2) and an algorithm for construction (Section 3.3). Case Study for Preference Statements: We describe a satisfaction system similar to that of Wilson et al.(2015) for modelling preferences (Section 4.1), prove that existence and uniqueness of a MG is not guaranteed under this system (Section 4.2), and complexity results of deciding the consistency of preferences and existence of a MG (Section 4.3) for hierarchical models and the special case of lexicographic models. |
| Researcher Affiliation | Academia | Anne-Marie George , Ana Ozaki University of Oslo, Norway EMAIL |
| Pseudocode | Yes | Algorithm 1: Middle Ground for Statements. Algorithm 2: Existence of Middle Ground. |
| Open Source Code | No | The paper does not provide any statement or link regarding the availability of source code for the described methodology. |
| Open Datasets | No | The paper is theoretical and focuses on conceptual and mathematical contributions, including algorithms and complexity analysis. It uses examples and refers to prior work involving datasets (e.g., Moral Machine Experiment, kidney exchanges) but does not conduct its own experiments using these or any other dataset, hence no access information for datasets used in its own work is provided. |
| Dataset Splits | No | The paper is theoretical and does not perform empirical evaluations using datasets. Therefore, no information on dataset splits is provided. |
| Hardware Specification | No | The paper is theoretical and focuses on algorithms, proofs, and complexity analysis. It does not describe any empirical experiments that would require specific hardware specifications. |
| Software Dependencies | No | The paper is theoretical and focuses on algorithms and complexity analysis, not empirical experiments. Therefore, no specific ancillary software details with version numbers are provided. |
| Experiment Setup | No | The paper is theoretical, presenting conceptual frameworks, algorithms, and complexity results. It does not describe any empirical experiments that would involve hyperparameter settings or training configurations. |