---
title: "Quota and Gmin Merging Operators"
authors:
  - "Patricia Everaere"
  - "Sébastien Konieczny"
  - "Pierre Marquis"
doi: ""
url: "https://ijcai.org/proceedings/2005/83"
pdf: "https://ijcai.org/proceedings/2005/0083.pdf"
venue: "Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence"
year: 2005
pages: "424-428"
track: ""
keywords:
---

# Quota and Gmin Merging Operators

Patricia Everaere, Sébastien Konieczny, Pierre Marquis

*Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence*, pages 424-428.

## Abstract

In this paper, two families of merging operators are considered: quota operators and Gmin operators. Quota operators rely on a simple idea: any possible world is viewed as a model of the result of the merging when it satisfies “sufficiently many” bases from the given profile (a multi-set of bases). Different interpretations of the “sufficiently many” give rise to specific operators. Each Gmin operator is parameterized by a pseudo-distance and each of them is intended to refine the quota operators (i.e., to preserve more information). Quota and Gmin operators are evaluated and compared along four dimensions: rationality, computational complexity, strategy-proofness, and discriminating power. Those two families are shown as interesting alternatives to the formula-based merging operators (which selects some formulas in the union of the bases).