Parliamentary Voting Procedures: Agenda Control, Manipulation, and Uncertainty
Authors: Robert Bredereck, Jiehua Chen, Rolf Niedermeier, Toby Walsh
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our polynomial-time algorithms leave open how many alternatives can win through control (or manipulation). We therefore use the data from Preflib due to Mattei and Walsh [2013] to investigate empirically the likelihood of successful manipulation or agenda control. Since only one case of the possible and the necessary winner problems is polynomial-time solvable and since Preflib offers only a very restricted variant of incomplete preferences, we do not run experiments for these two problems. Our results are shown in Table 2. |
| Researcher Affiliation | Academia | 1Institut f ur Softwaretechnik und Theoretische Informatik, TU Berlin, Germany {robert.bredereck, jiehua.chen, rolf.niedermeier}@tu-berlin.de 2NICTA and the University of New South Wales, Australia toby.walsh@nicta.com.au |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks (clearly labeled algorithm sections or code-like formatted procedures). |
| Open Source Code | No | The paper does not provide concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described in this paper. |
| Open Datasets | Yes | We therefore use the data from Preflib due to Mattei and Walsh [2013] to investigate empirically the likelihood of successful manipulation or agenda control. |
| Dataset Splits | No | The paper does not provide specific dataset split information (exact percentages, sample counts, citations to predefined splits, or detailed splitting methodology) needed to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers like Python 3.8, CPLEX 12.4) needed to replicate the experiment. |
| Experiment Setup | No | The paper does not contain specific experimental setup details (concrete hyperparameter values, training configurations, or system-level settings) in the main text. |