TY - GEN
T1 - Mechanism Design for Facility Location Problems
T2 - 30th International Joint Conference on Artificial Intelligence, IJCAI 2021
AU - Chan, Hau
AU - Filos-Ratsikas, Aris
AU - Li, Bo
AU - Li, Minming
AU - Wang, Chenhao
N1 - Publisher Copyright:
© 2021 International Joint Conferences on Artificial Intelligence. All rights reserved.
PY - 2021
Y1 - 2021
N2 - The study of approximate mechanism design for facility location problems has been in the center of research at the intersection of artificial intelligence and economics for the last decades, largely due to its practical importance in various domains, such as social planning and clustering. At a high level, the goal is to design mechanisms to select a set of locations on which to build a set of facilities, aiming to optimize some social objective and ensure desirable properties based on the preferences of strategic agents, who might have incentives to misreport their private information such as their locations. This paper presents a comprehensive survey of the significant progress that has been made since the introduction of the problem, highlighting the different variants and methodologies, as well as the most interesting directions for future research.
AB - The study of approximate mechanism design for facility location problems has been in the center of research at the intersection of artificial intelligence and economics for the last decades, largely due to its practical importance in various domains, such as social planning and clustering. At a high level, the goal is to design mechanisms to select a set of locations on which to build a set of facilities, aiming to optimize some social objective and ensure desirable properties based on the preferences of strategic agents, who might have incentives to misreport their private information such as their locations. This paper presents a comprehensive survey of the significant progress that has been made since the introduction of the problem, highlighting the different variants and methodologies, as well as the most interesting directions for future research.
UR - https://www.scopus.com/pages/publications/85124405556
U2 - 10.24963/ijcai.2021/596
DO - 10.24963/ijcai.2021/596
M3 - 会议稿件
AN - SCOPUS:85124405556
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 4356
EP - 4365
BT - Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021
A2 - Zhou, Zhi-Hua
PB - International Joint Conferences on Artificial Intelligence
Y2 - 19 August 2021 through 27 August 2021
ER -