TY - GEN
T1 - Two-Sided Matching over Social Networks
AU - Cho, Sung Ho
AU - Todo, Taiki
AU - Yokoo, Makoto
N1 - Funding Information:
This work is partially supported by JSPS KAKENHI Grant Numbers JP20H00587, JP20H00609, and JP21H04979, and Grant-in-Aid for “2019 Initiative for Realizing Diversity in the Research Environment” through the “Diversity and Super Global Training Program for Female and Young Faculty (SENTAN-Q),” Kyushu University from MEXT.
Publisher Copyright:
© 2022 International Joint Conferences on Artificial Intelligence. All rights reserved.
PY - 2022
Y1 - 2022
N2 - A new paradigm of mechanism design, called mechanism design over social networks, investigates agents' incentives to diffuse the information of mechanisms to their followers over social networks. In this paper we consider it for two-sided matching, where the agents on one side, say students, are distributed over social networks and thus are not fully observable to the mechanism designer, while the agents on the other side, say colleges, are known a priori. The main purpose of this paper is to clarify the existence of mechanisms that satisfy several properties that are classified into four criteria: incentive constraints, efficiency constraints, stability constraints, and fairness constraints. We proposed three mechanisms and showed that no mechanism is better than these mechanisms, i.e., they are in the Pareto frontier according to the set of properties defined in this paper.
AB - A new paradigm of mechanism design, called mechanism design over social networks, investigates agents' incentives to diffuse the information of mechanisms to their followers over social networks. In this paper we consider it for two-sided matching, where the agents on one side, say students, are distributed over social networks and thus are not fully observable to the mechanism designer, while the agents on the other side, say colleges, are known a priori. The main purpose of this paper is to clarify the existence of mechanisms that satisfy several properties that are classified into four criteria: incentive constraints, efficiency constraints, stability constraints, and fairness constraints. We proposed three mechanisms and showed that no mechanism is better than these mechanisms, i.e., they are in the Pareto frontier according to the set of properties defined in this paper.
UR - http://www.scopus.com/inward/record.url?scp=85137909512&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85137909512&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85137909512
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 186
EP - 193
BT - Proceedings of the 31st International Joint Conference on Artificial Intelligence, IJCAI 2022
A2 - De Raedt, Luc
A2 - De Raedt, Luc
PB - International Joint Conferences on Artificial Intelligence
T2 - 31st International Joint Conference on Artificial Intelligence, IJCAI 2022
Y2 - 23 July 2022 through 29 July 2022
ER -