Ex-post max-min fairness of generalized AGV mechanisms
Ex-post max-min fairness of generalized AGV mechanisms
We generalize the standard Arrow-d'Aspremont-Gerard-Varet (AGV) mechanism to balance the net payoffs received by all agents, while maintaining Bayesian incentive compatibility, ex-post efficiency, and ex-post budget balance of the standard AGV mechanism. In a private-value setting with independent agents' types and the principal's cost, we formulate a convex optimization problem to find the mechanism (that achieves ex-post max-min fairness) over a set of parameterized generalized AGV mechanisms, through maximizing the expected value of the minimum ex-post net payoff. We reformulate the convex program as a linear program that can be effectively solved when the number of agents is small. When the number of agents is large, we propose to solve the formulated convex program through the incremental subgradient method. Numerical results on two action models show that the proposed mechanism significantly outperforms the standard AGV mechanism in terms of the expected minimum ex-post payoff.
Arrow-d'Aspremont-Gerard-Varet (AGV)
5275-5281
Wang, Tao
2fb73f3e-d9a8-45cd-901d-663ba743b9ac
Xu, Yunjian
cfd9a269-b7d7-42c0-9ade-b201e1a6d400
Ahipasaoglu, Selin Damla
d69f1b80-5c05-4d50-82df-c13b87b02687
Courcoubetis, Costas
e5055b1c-6410-48f8-9693-320c9e930fa2
October 2017
Wang, Tao
2fb73f3e-d9a8-45cd-901d-663ba743b9ac
Xu, Yunjian
cfd9a269-b7d7-42c0-9ade-b201e1a6d400
Ahipasaoglu, Selin Damla
d69f1b80-5c05-4d50-82df-c13b87b02687
Courcoubetis, Costas
e5055b1c-6410-48f8-9693-320c9e930fa2
Wang, Tao, Xu, Yunjian, Ahipasaoglu, Selin Damla and Courcoubetis, Costas
(2017)
Ex-post max-min fairness of generalized AGV mechanisms.
IEEE Transactions on Automatic Control, 62 (10), .
(doi:10.1109/TAC.2016.2632424).
Abstract
We generalize the standard Arrow-d'Aspremont-Gerard-Varet (AGV) mechanism to balance the net payoffs received by all agents, while maintaining Bayesian incentive compatibility, ex-post efficiency, and ex-post budget balance of the standard AGV mechanism. In a private-value setting with independent agents' types and the principal's cost, we formulate a convex optimization problem to find the mechanism (that achieves ex-post max-min fairness) over a set of parameterized generalized AGV mechanisms, through maximizing the expected value of the minimum ex-post net payoff. We reformulate the convex program as a linear program that can be effectively solved when the number of agents is small. When the number of agents is large, we propose to solve the formulated convex program through the incremental subgradient method. Numerical results on two action models show that the proposed mechanism significantly outperforms the standard AGV mechanism in terms of the expected minimum ex-post payoff.
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e-pub ahead of print date: 23 December 2016
Published date: October 2017
Keywords:
Arrow-d'Aspremont-Gerard-Varet (AGV)
Identifiers
Local EPrints ID: 443188
URI: http://eprints.soton.ac.uk/id/eprint/443188
ISSN: 0018-9286
PURE UUID: 74a3d31f-a6ae-4293-b18e-cbb739c706cb
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Date deposited: 13 Aug 2020 16:38
Last modified: 17 Mar 2024 04:03
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Contributors
Author:
Tao Wang
Author:
Yunjian Xu
Author:
Costas Courcoubetis
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