Results 1 
3 of
3
Truthful Mechanisms for OneParameter Agents
"... In this paper, we show how to design truthful (dominant strategy) mechanisms for several combinatorial problems where each agent’s secret data is naturally expressed by a single positive real number. The goal of the mechanisms we consider is to allocate loads placed on the agents, and an agent’s sec ..."
Abstract

Cited by 191 (4 self)
 Add to MetaCart
In this paper, we show how to design truthful (dominant strategy) mechanisms for several combinatorial problems where each agent’s secret data is naturally expressed by a single positive real number. The goal of the mechanisms we consider is to allocate loads placed on the agents, and an agent’s secret data is the cost she incurs per unit load. We give an exact characterization for the algorithms that can be used to design truthful mechanisms for such load balancing problems using appropriate side payments. We use our characterization to design polynomial time truthful mechanisms for several problems in combinatorial optimization to which the celebrated VCG mechanism does not apply. For scheduling related parallel machines (QjjCmax), we give a 3approximation mechanism based on randomized rounding of the optimal fractional solution. This problem is NPcomplete, and the standard approximation algorithms (greedy loadbalancing or the PTAS) cannot be used in truthful mechanisms. We show our mechanism to be frugal, in that the total payment needed is only a logarithmic factor more than the actual costs incurred by the machines, unless one machine dominates the total processing power. We also give truthful mechanisms for maximum flow, Qjj P Cj (scheduling related machines to minimize the sum of completion times), optimizing an affine function over a fixed set, and special cases of uncapacitated facility location. In addition, for Qjj P wjCj (minimizing the weighted sum of completion times), we prove a lower bound of 2 p 3 for the best approximation ratio achievable by a truthful mechanism.
Frugal path mechanisms
, 2002
"... We consider the problem of selecting a low cost s − t path in a graph, where the edge costs are a secret known only to the various economic agents who own them. To solve this problem, Nisan and Ronen applied the celebrated VickreyClarkeGroves (VCG) mechanism, which pays a premium to induce the edg ..."
Abstract

Cited by 115 (2 self)
 Add to MetaCart
We consider the problem of selecting a low cost s − t path in a graph, where the edge costs are a secret known only to the various economic agents who own them. To solve this problem, Nisan and Ronen applied the celebrated VickreyClarkeGroves (VCG) mechanism, which pays a premium to induce the edges to reveal their costs truthfully. We observe that this premium can be unacceptably high. There are simple instances where the mechanism pays Θ(k) times the actual cost of the path, even if there is an alternate path available that costs only (1 + ɛ) times as much. This inspires the frugal path problem, which is to design a mechanism that selects a path and induces truthful cost revelation without paying such a high premium. This paper contributes negative results on the frugal path problem. On two large classes of graphs, including ones having three nodedisjoint s − t paths, we prove that no reasonable mechanism can always avoid paying a high premium to induce truthtelling. In particular, we introduce a general class of min function mechanisms, and show that all min function mechanisms can be forced to overpay just as badly as VCG. On the other hand, we prove that (on two large classes of graphs) every truthful mechanism satisfying some reasonable properties is a min function mechanism. 1
Deriving Consensus in Multiagent Systems
 Artificial Intelligence
, 1996
"... the rules by which agents in an encounter will interact. Once the rules of encounter have been determined, each builder of each agent is free to design his own machine any way that he wants. However, the rules that were established will certainly affect the choices he makes in building his own ag ..."
Abstract

Cited by 32 (2 self)
 Add to MetaCart
the rules by which agents in an encounter will interact. Once the rules of encounter have been determined, each builder of each agent is free to design his own machine any way that he wants. However, the rules that were established will certainly affect the choices he makes in building his own agent.