TY - GEN
T1 - Fairness and Incentive Compatibility via Percentage Fees
AU - Dobzinski, Shahar
AU - Oren, Sigal
AU - Vondrak, Jan
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/7/9
Y1 - 2023/7/9
N2 - We study incentive-compatible mechanisms that maximize the Nash Social Welfare. Since traditional incentive-compatible mechanisms cannot maximize the Nash Social Welfare even approximately, we propose changing the traditional model. Inspired by a widely used charging method (e.g., royalties, a lawyer that charges some percentage of possible future compensation), we suggest charging the players some percentage of their value of the outcome. We call this model the percentage fee model.We show that there is a mechanism that maximizes exactly the Nash Social Welfare in every setting with non-negative valuations. Moreover, we prove an analog of Roberts theorem that essentially says that if the valuations are non-negative, then the only implementable social choice functions are those that maximize weighted variants of the Nash Social Welfare. We develop polynomial time incentive compatible approximation algorithms for the Nash Social Welfare with subadditive valuations and prove some hardness results.
AB - We study incentive-compatible mechanisms that maximize the Nash Social Welfare. Since traditional incentive-compatible mechanisms cannot maximize the Nash Social Welfare even approximately, we propose changing the traditional model. Inspired by a widely used charging method (e.g., royalties, a lawyer that charges some percentage of possible future compensation), we suggest charging the players some percentage of their value of the outcome. We call this model the percentage fee model.We show that there is a mechanism that maximizes exactly the Nash Social Welfare in every setting with non-negative valuations. Moreover, we prove an analog of Roberts theorem that essentially says that if the valuations are non-negative, then the only implementable social choice functions are those that maximize weighted variants of the Nash Social Welfare. We develop polynomial time incentive compatible approximation algorithms for the Nash Social Welfare with subadditive valuations and prove some hardness results.
UR - http://www.scopus.com/inward/record.url?scp=85168113207&partnerID=8YFLogxK
U2 - 10.1145/3580507.3597810
DO - 10.1145/3580507.3597810
M3 - Conference contribution
AN - SCOPUS:85168113207
T3 - EC 2023 - Proceedings of the 24th ACM Conference on Economics and Computation
SP - 517
EP - 535
BT - EC 2023 - Proceedings of the 24th ACM Conference on Economics and Computation
PB - Association for Computing Machinery, Inc
T2 - 24th ACM Conference on Economics and Computation, EC 2023
Y2 - 9 July 2023 through 12 July 2023
ER -