Sari la conținut

Română · beta. Traducerea a fost făcută automat și este încă în curs de revizuire. Citește pagina în engleză

În afara temei aiqbench

În afara temei aiqbench

Această știre a fost preluată de la o sursă pe care o urmărim, dar nu ține de domeniul AI sau cuantic, așa că nu există o perspectivă aiqbench pentru ea.

Participatory Budgeting with Project Groups

arXiv2 min de cititArticolul și perspectiva sunt în engleză.

arXiv:2012.05213v2 Announce Type: replace-cross Abstract: We study a generalization of the standard approval-based model of participatory budgeting (PB), in which voters are providing approval ballots over a set of predefined projects and---in addition to a global budget limit, there are several groupings of the projects, each group with its own budget limit. We study the computational complexity of identifying project bundles that maximize voter satisfaction while respecting all budget limits. We show that the problem is generally intractable and describe efficient exact algorithms for several special cases, including instances with only few groups and instances where the group structure is close to be hierarchical, as well as efficient approximation algorithms. Our results could allow, e.g., municipalities to hold richer PB processes that are thematically and geographically inclusive.

Abstract:We study a generalization of the standard approval-based model of participatory budgeting (PB), in which voters are providing approval ballots over a set of predefined projects and---in addition to a global budget limit, there are several groupings of the projects, each group with its own budget limit. We study the computational complexity of identifying project bundles that maximize voter satisfaction while respecting all budget limits. We show that the problem is generally intractable and describe efficient exact algorithms for several special cases, including instances with only few groups and instances where the group structure is close to be hierarchical, as well as efficient approximation algorithms. Our results could allow, e.g., municipalities to hold richer PB processes that are thematically and geographically inclusive.

25 pages, 3 tables. An extended abstract of this work appears in IJCAI 2021. This is the author's version of the paper published in JCSS 156: 103702 (2026); it differs only in formatting and minor editorial changes

Computer Science and Game Theory (cs.GT); Artificial Intelligence (cs.AI); Data Structures and Algorithms (cs.DS); Multiagent Systems (cs.MA)

arXiv:2012.05213 [cs.GT]

(or arXiv:2012.05213v2 [cs.GT] for this version)

https://doi.org/10.1016/j.jcss.2025.103702 DOI(s) linking to related resources

Text integral sub licența deschisă a publicației · 190 cuvinte

Subiecte conexe