On Recognising Nearly Single-Crossing Preferences

Authors: Florian Jaeckle, Dominik Peters, Edith Elkind

AAAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical We prove that it can be efficiently decided if voters can be split into two single-crossing groups. Also, for every fixed k ≥ 1 we can decide in polynomial time if a profile can be made single-crossing by performing at most k candidate swaps per vote. In contrast, for each k ≥ 3 it is NP-complete to decide whether candidates can be partitioned into k sets so that the restriction of the input profile to each set is single-crossing. Our results are summarised in Table 1.
Researcher Affiliation Academia Florian Jaeckle, Dominik Peters, Edith Elkind Department of Computer Science University of Oxford, UK
Pseudocode No The paper describes algorithms in prose, for example, 'Our algorithm proceeds by creating and solving several instances of 2SAT', but it does not include formally structured pseudocode or algorithm blocks.
Open Source Code No The paper does not provide any statement about the availability of open-source code for the described methodology.
Open Datasets No This paper is theoretical research and does not use or provide access to any dataset for training.
Dataset Splits No This paper is theoretical research and does not specify any dataset splits for validation.
Hardware Specification No This paper is theoretical research and does not describe any specific hardware used for running experiments.
Software Dependencies No This paper is theoretical research and does not specify any software dependencies with version numbers.
Experiment Setup No This paper is theoretical research and does not describe any experimental setup details such as hyperparameters or training configurations.