TY - GEN
T1 - Participatory Budgeting
T2 - 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
AU - Faliszewski, Piotr
AU - Flis, Jarosław
AU - Peters, Dominik
AU - Pierczyński, Grzegorz
AU - Skowron, Piotr
AU - Stolicki, Dariusz
AU - Szufa, Stanisław
AU - Talmon, Nimrod
N1 - Funding Information:
was supported by NCN project 2018/29/N/ST6/01303. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 101002854).
Funding Information:
Grzegorz Pierczyński and Piotr Skowron were supported by Poland's National Science Center grant no. 2019/35/B/ST6/02215. Nimrod Talmon has been supported by the Israel Science Foundation (grant No. 630/19). Dariusz Stolicki was supported by Poland's National Science Center grant no. 2019/35/B/HS5/03949 and Jagiellonian's University Excellence Initiative, project QuantPol. Stanisław Szufa was supported by NCN project 2018/29/N/ST6/01303. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 101002854).
Funding Information:
Grzegorz Pierczyński and Piotr Skowron were supported by Poland’s National Science Center grant no. 2019/35/B/ST6/02215. Nimrod Talmon has been supported by the Israel Science Foundation (grant No. 630/19). Dariusz Stolicki was supported by Poland’s National Science Center grant no. 2019/35/B/HS5/03949 and Jagiellonian’s University Excellence Initiative, project QuantPol. Stanisław Szufa
Publisher Copyright:
© 2023 International Joint Conferences on Artificial Intelligence. All rights reserved.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - We provide a library of participatory budgeting data (Pabulib) and open source tools (Pabutools and Pabustats) for analysing this data. We analyse how the results of participatory budgeting elections would change if a different selection rule was applied. We provide evidence that the outcomes of the Method of Equal Shares would be considerably fairer than those of the Utilitarian Greedy rule that is currently in use. We also show that the division of the projects into districts and/or categories can in many cases be avoided when using proportional rules. We find that this would increase the overall utility of the voters.
AB - We provide a library of participatory budgeting data (Pabulib) and open source tools (Pabutools and Pabustats) for analysing this data. We analyse how the results of participatory budgeting elections would change if a different selection rule was applied. We provide evidence that the outcomes of the Method of Equal Shares would be considerably fairer than those of the Utilitarian Greedy rule that is currently in use. We also show that the division of the projects into districts and/or categories can in many cases be avoided when using proportional rules. We find that this would increase the overall utility of the voters.
UR - http://www.scopus.com/inward/record.url?scp=85170380045&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85170380045
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 2667
EP - 2674
BT - Proceedings of the 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
A2 - Elkind, Edith
PB - International Joint Conferences on Artificial Intelligence
Y2 - 19 August 2023 through 25 August 2023
ER -