An Analytical and Experimental Comparison of Maximal Lottery Schemes
Authors: Florian Brandl, Felix Brandt, Christian Stricker
IJCAI 2018 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Furthermore, we evaluate the frequency of manipulable preference profiles and the degree of randomization of ML schemes via extensive computer simulations. |
| Researcher Affiliation | Academia | Florian Brandl, Felix Brandt, Christian Stricker Technische Universit at M unchen {brandlfl,brandtf,stricker}@in.tum.de |
| Pseudocode | No | The paper does not contain structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper mentions 'Easy-to-use voting tools for C1-ML and C2-ML are available on the websites votation.ovh (in French) and pnyx.dss.in.tum.de, respectively.' However, this refers to general tools for the schemes, not explicitly the source code for the methodology or simulations developed in this paper. |
| Open Datasets | No | The paper describes using the 'impartial anonymous culture (IAC)' model for generating preference profiles for simulations, which is a stochastic model, not a public dataset with access information provided. |
| Dataset Splits | No | The paper does not provide specific dataset split information (e.g., percentages, sample counts for train/validation/test splits). |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., GPU/CPU models, memory) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details with version numbers needed to replicate the experiment. |
| Experiment Setup | Yes | For these experiments, we confined ourselves to profiles with an odd number of agents with strict preferences. The stochastic preference model used for our experiments is called impartial anonymous culture (IAC). Under IAC, preference profiles form equivalence classes with two profiles belonging to the same class if they are identical up to permutations of the agents. Every equivalence class is assumed to be equally likely. ... For 100.000 samples for every combination of parameters according to the IAC model. ... Each point is based on 2000 preference profiles sampled according to the IAC model and on testing all possible deviations for each type of voter. |