A Parameterized Complexity Analysis of Generalized CP-Nets
Authors: Martin Kronegger, Martin Lackner, Andreas Pfandler, Reinhard Pichler
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We have studied this question experimentally by randomly generating conditional preference rules... Figure 1 shows the average values of the diameter, the maximum diameter and the average distance in GCP-nets with 12 variables. |
| Researcher Affiliation | Academia | Martin Kronegger, Martin Lackner, Andreas Pfandler, and Reinhard Pichler Vienna University of Technology, Austria {kronegger, lackner, pfandler, pichler}@dbai.tuwien.ac.at |
| Pseudocode | No | No pseudocode or clearly labeled algorithm block was found in the paper. The paper focuses on theoretical complexity analysis and proofs. |
| Open Source Code | No | The paper does not contain any explicit statement about releasing source code for the described methodology, nor does it provide a link to a code repository. |
| Open Datasets | No | The paper describes generating synthetic data ('randomly generating conditional preference rules') for its experimental studies rather than using a publicly available or open dataset. No concrete access information for a dataset is provided. |
| Dataset Splits | No | The paper's experimental section focuses on characterizing properties of randomly generated GCP-nets, not on training or evaluating a model. Therefore, no explicit training/validation/test dataset splits are described. |
| Hardware Specification | No | The paper does not provide any specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments or computations. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library names or solver versions, that would be needed to replicate the experiments or theoretical computations. |
| Experiment Setup | Yes | We have investigated the relationship between the number of conditional preferences rules and the diameter. For each number of rules we have generated 100 GCP-nets randomly and calculated the diameter and the average distance between any two vertices in the preference graph. |