Year: 2021
Type: preprint
Abstract: Many important collective decision-making problems can be seen as multi-agent versions of discrete optimisation problems. Participatory budgeting, for instance, is the collective version of the knapsack problem; other examples include collective scheduling, and collective spanning trees. Rather than developing a specific model, as well as specific algorithmic techniques, for each of these problems, we propose to represent and solve them in the unifying framework of judgment aggregation with weighted issues. We provide a modular definition of collective discrete optimisation (CDO) rules based on coupling a set scoring function with an operator, and we show how they generalise several existing procedures developed for specific CDO problems. We also give an implementation based on integer linear programming (ILP) and test it on the problem of collective spanning trees.
Source: arXiv (Cornell University)
Institutions: Heinrich Heine University Düsseldorf, Université Paris 1 Panthéon-Sorbonne, Institut de Recherche en Informatique de Toulouse, Université de Toulouse, Centre National de la Recherche Scientifique, Université Paris Sciences et Lettres, Université Paris Dauphine-PSL, Université Paris Cité, Centre d'Économie de la Sorbonne
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W3217233597