TY - JOUR
T1 - Achieving allocatively-efficient and strongly budget-balanced mechanisms in the network flow domain for bounded-rational agents
AU - Bachrach, Yoram
AU - Rosenschein, Jeffrey S.
PY - 2005
Y1 - 2005
N2 - Vickrey-Clarke-Groves (VCG) mechanisms are a framework for finding a solution to a distributed optimization problem in systems of self-interested agents. VCG mechanisms have received wide attention in the AI community because they are efficient and strategy-proof; a special case of the Groves family of mechanisms, VCG mechanisms are the only direct-revelation mechanisms that are allocatively efficient and strategy-proof. Unfortunately, they are only weakly budget-balanced. We consider self-interested agents in a network flow domain, and show that in this domain, it is possible to design a mechanism that is both allocatively-efficient and almost completely budget-balanced. This is done by choosing a mechanism that is not strategy-proof but rather strategy-resistant. Instead of using the VCG mechanism, we propose a mechanism in which finding a beneficial manipulation is an NP-complete problem, and the payments from the agents to the mechanism may be minimized as much as desired.
AB - Vickrey-Clarke-Groves (VCG) mechanisms are a framework for finding a solution to a distributed optimization problem in systems of self-interested agents. VCG mechanisms have received wide attention in the AI community because they are efficient and strategy-proof; a special case of the Groves family of mechanisms, VCG mechanisms are the only direct-revelation mechanisms that are allocatively efficient and strategy-proof. Unfortunately, they are only weakly budget-balanced. We consider self-interested agents in a network flow domain, and show that in this domain, it is possible to design a mechanism that is both allocatively-efficient and almost completely budget-balanced. This is done by choosing a mechanism that is not strategy-proof but rather strategy-resistant. Instead of using the VCG mechanism, we propose a mechanism in which finding a beneficial manipulation is an NP-complete problem, and the payments from the agents to the mechanism may be minimized as much as desired.
UR - http://www.scopus.com/inward/record.url?scp=33750987884&partnerID=8YFLogxK
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AN - SCOPUS:33750987884
SN - 1045-0823
SP - 1653
EP - 1654
JO - IJCAI International Joint Conference on Artificial Intelligence
JF - IJCAI International Joint Conference on Artificial Intelligence
T2 - 19th International Joint Conference on Artificial Intelligence, IJCAI 2005
Y2 - 30 July 2005 through 5 August 2005
ER -