Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Possible and Necessary Winners of Partial Tournaments
Authors: Haris Aziz, Markus Brill, Felix Fischer, Paul Harrenstein, Jerome Lang, Hans Georg Seedig
JAIR 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Our results are encouraging, in the sense that most of the problems can be solved in polynomial time. Table 1 summarizes our findings. Similar problems have been considered before. For Condorcet winners, voting trees and the top cycle, it has been shown that possible and necessary winners are computable in polynomial time (Konczak & Lang, 2005; Lang et al., 2012). The same holds for the computation of possible Copeland winners, a problem that has been considered in the context of sports tournaments (Cook, Cunningham, Pulleyblank, & Schrijver, 1998). |
| Researcher Affiliation | Academia | Haris Aziz EMAIL Data61 and University of New South Wales Australia Markus Brill EMAIL Computer Science Department Duke University, USA Felix Fischer EMAIL Institut f ur Mathematik Technische Universit at Berlin, Germany Paul Harrenstein EMAIL Computer Science Department University of Oxford, UK J erˆome Lang EMAIL LAMSADE Universit e Paris-Dauphine, France Hans Georg Seedig EMAIL Institut f ur Informatik Technische Universit at M unchen, Germany |
| Pseudocode | No | The paper describes various algorithms and proofs of computational complexity, for example, in the Proof of Theorem 8, it outlines a polynomial-time algorithm. However, these algorithms are described in prose and mathematical notation rather than structured pseudocode blocks or explicitly labeled algorithm figures. |
| Open Source Code | No | The paper is theoretical, focusing on computational complexity and proofs for problems related to partial tournaments. There is no mention or statement about releasing source code for the methodologies described in the paper. |
| Open Datasets | No | The paper deals with theoretical concepts of partial and weighted tournaments. It does not involve empirical experiments using specific datasets; rather, it analyzes the computational properties of abstract tournament structures. Therefore, no public or open datasets are mentioned or provided. |
| Dataset Splits | No | The paper is purely theoretical, focusing on computational complexity analysis and proofs. It does not conduct experiments on datasets, and thus, there is no mention of dataset splits such as training, validation, or test sets. |
| Hardware Specification | No | The paper is theoretical in nature, focusing on the computational complexity of determining winners in partial tournaments. It does not describe any experimental setup or implementations that would require specific hardware specifications. |
| Software Dependencies | No | The paper is a theoretical work on computational complexity. It does not describe any implementation details, software development, or require specific software dependencies with version numbers for its methodology. |
| Experiment Setup | No | The paper is theoretical, centered on computational complexity, algorithms, and proofs related to tournament solutions. It does not describe any empirical experiments, and therefore, there are no details on experimental setups, hyperparameters, or training configurations. |