Online Approval Committee Elections

• URL: http://arxiv.org/abs/2202.06830v1
• Date: Mon, 14 Feb 2022 16:06:47 GMT
• Title: Online Approval Committee Elections
• Authors: Virginie Do, Matthieu Hervouin, J\'er\^ome Lang, Piotr Skowron
• Abstract summary: We show how to compute committees with maximal expected score. We assume $k$ candidates need to be selected. The candidates appear over time. Each time one appears, it must be immediately selected or rejected.
• Score: 20.217228946041168
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Assume $k$ candidates need to be selected. The candidates appear over time. Each time one appears, it must be immediately selected or rejected -- a decision that is made by a group of individuals through voting. Assume the voters use approval ballots, i.e., for each candidate they only specify whether they consider it acceptable or not. This setting can be seen as a voting variant of choosing $k$ secretaries. Our contribution is twofold. (1) We assess to what extent the committees that are computed online can proportionally represent the voters. (2) If a prior probability over candidate approvals is available, we show how to compute committees with maximal expected score.

Related papers

• ElectionSim: Massive Population Election Simulation Powered by Large Language Model Driven Agents [70.17229548653852]
  We introduce ElectionSim, an innovative election simulation framework based on large language models. We present a million-level voter pool sampled from social media platforms to support accurate individual simulation. We also introduce PPE, a poll-based presidential election benchmark to assess the performance of our framework under the U.S. presidential election scenario.
  arXiv  Detail & Related papers  (2024-10-28T05:25:50Z)
• Improving the Computational Efficiency of Adaptive Audits of IRV Elections [54.427049258408424]
  AWAIRE can audit IRV contests with any number of candidates, but the original implementation incurred memory and computation costs that grew superexponentially with the number of candidates. This paper improves the algorithmic implementation of AWAIRE in three ways that make it practical to audit IRV contests with 55 candidates, compared to the previous 6 candidates.
  arXiv  Detail & Related papers  (2024-07-23T13:28:00Z)
• Adaptively Weighted Audits of Instant-Runoff Voting Elections: AWAIRE [61.872917066847855]
  Methods for auditing instant-runoff voting (IRV) elections are either not risk-limiting or require cast vote records (CVRs), the voting system's electronic record of the votes on each ballot. We develop an RLA method that uses adaptively weighted averages of test supermartingales to efficiently audit IRV elections when CVRs are not available.
  arXiv  Detail & Related papers  (2023-07-20T15:55:34Z)
• Risk-Limiting Audits for Condorcet Elections [27.102139020324678]
  We show how we can efficiently audit Condorcet elections for a number of variations. We also compare the audit efficiency (how many ballots we expect to sample) of IRV and Condorcet elections.
  arXiv  Detail & Related papers  (2023-03-18T22:08:17Z)
• Diverse Representation via Computational Participatory Elections -- Lessons from a Case Study [16.699381591572166]
  We have designed a novel participatory electoral process coined the Representation Pact, implemented with the support of a computational system. That process explicitly enables voters to decide on representation criteria in a first round, and then lets them vote for candidates in a second round. After the two rounds, a counting method is applied, which selects the committee of candidates that maximizes the number of votes received in the second round.
  arXiv  Detail & Related papers  (2022-05-30T19:22:38Z)
• Expected Frequency Matrices of Elections: Computation, Geometry, and Preference Learning [58.23459346724491]
  We use the "map of elections" approach of Szufa et al. (AAMAS 2020) to analyze several well-known vote distributions. We draw the "skeleton map" of distributions, evaluate its robustness, and analyze its properties.
  arXiv  Detail & Related papers  (2022-05-16T17:40:22Z)
• DiRe Committee : Diversity and Representation Constraints in Multiwinner Elections [0.0]
  We develop a model, DiRe Committee Winner Determination (DRCWD), which delineates candidate and voter attributes to select a committee. We develop a feasibility-based algorithm, which finds the winning DiRe committee in under two minutes on 63% of the instances of synthetic datasets and on 100% of instances of real-world datasets. Overall, DRCWD motivates that a study of multiwinner elections should consider both its actors, namely candidates and voters, as candidate-specific "fair" models can unknowingly harm voter populations, and vice versa.
  arXiv  Detail & Related papers  (2021-07-15T14:32:56Z)
• Bribery as a Measure of Candidate Success: Complexity Results for Approval-Based Multiwinner Rules [58.8640284079665]
  We study the problem of bribery in multiwinner elections, for the case where the voters cast approval ballots (i.e., sets of candidates they approve) We consider a number of approval-based multiwinner rules (AV, SAV, GAV, RAV, approval-based Chamberlin--Courant, and PAV) In general, our problems tend to be easier when we limit out bribery actions on increasing the number of approvals of the candidate that we want to be in a winning committee.
  arXiv  Detail & Related papers  (2021-04-19T08:26:40Z)
• MS-Ranker: Accumulating Evidence from Potentially Correct Candidates for Answer Selection [59.95429407899612]
  We propose a novel reinforcement learning based multi-step ranking model, named MS-Ranker. We explicitly consider the potential correctness of candidates and update the evidence with a gating mechanism. Our model significantly outperforms existing methods that do not rely on external resources.
  arXiv  Detail & Related papers  (2020-10-10T10:36:58Z)
• Representative Committees of Peers [21.26271260313741]
  We show that a k-sortition leads to an outcome within the factor 1+O (1/k) of the optimal social cost for any number of voters. For large issues, we demonstrate that the k-sortition is the worst-case optimal rule within a broad family of committee-based rules.
  arXiv  Detail & Related papers  (2020-06-14T08:20:47Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.