Optimizing Viscous Democracy
Authors: Ben Armstrong, Shiri Alouf-Heffetz, Nimrod Talmon
IJCAI 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | In this paper we adopt a dual approach, employing analytical and theoretical methodologies, as well as computer-based simulations. Theoretical analyses provide insights into the fundamental dynamics and properties of viscous democracy; simulations, on the other hand, offer a tangible platform for observing the empirical behavior of viscous democracy under varied conditions, facilitating a more realistic assessment of its outcomes and interactions. |
| Researcher Affiliation | Academia | Ben Armstrong1 , Shiri Alouf-Heffetz2 , Nimrod Talmon2 1University of Waterloo 2Ben-Gurion University ben.armstrong@uwateralo.ca, shirihe@post.bgu.ac.il, talmonn@bgu.ac.il |
| Pseudocode | Yes | Algorithm 1 Competence-Based Attachment (CBA) Input: V, Q, G 1: S G 2: E 3: D (V, E) 4: while S = V do 5: Select one voter vi V \ S uniformly at random. 6: Select one voter vj S with probability proportional to its relative competence; P(vj) qj P 7: Attach: E E (vi, vj). 8: Update: S S {vi}. 9: end while |
| Open Source Code | No | The paper does not contain an explicit statement about the release of source code for the described methodology, nor does it provide a direct link to a code repository. |
| Open Datasets | No | The paper mentions using empirical networks detailed in a reference that is a preprint of this same paper, and discusses randomly generated networks, but does not provide concrete access information (link, DOI, specific repository, or formal citation for external datasets) for any dataset used. |
| Dataset Splits | No | The paper describes simulation-based experiments rather than using fixed datasets with traditional train/validation/test splits. Therefore, information about such splits is not applicable or provided. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU/CPU models, memory) used to run the experiments. |
| Software Dependencies | No | The paper mentions using "Sci Py implementation" but does not provide specific version numbers for this or any other software dependencies. |
| Experiment Setup | Yes | Each reported accuracy result is the proportion of 1000 elections in which a+ was successfully elected, following the same procedure as Alouf-Heffetz et al..", "we calculate accuracy several times at 21 evenly spaced values of α in [0, 1] (chosen to test at every interval of 0.05).", "Each point represents 50 trials with 100 voters each.", "For each delegation mechanism and competence distribution, we ran 300 trials on randomly generated ER and BA social networks.", "competencies drawn from one of 3 distributions... (i) Uniform Intervals of width 0.2 from U (0, 0.2) shifted up to U (0.8, 1) in equal steps of 0.1. (ii) Gaussian µ {0.1, 0.2, ..., 0.9}, σ = 0.051 (iii) Exponential µ {0.1, 0.2, ..., 0.9}2 |