Setting lower bounds on truthfulness

We present and discuss general techniques for proving inapproximability results for truthful mechanisms. We make use of these techniques to prove lower bounds on the approximability of several non-utilitarian multi-parameter problems. In particular, we demonstrate the strength of our techniques by e...

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Bibliographic Details
Main Author: Michael Schapira
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2007
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.104.6344
http://www.cs.huji.ac.il/~mikesch/scheduling.pdf
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Summary:We present and discuss general techniques for proving inapproximability results for truthful mechanisms. We make use of these techniques to prove lower bounds on the approximability of several non-utilitarian multi-parameter problems. In particular, we demonstrate the strength of our techniques by exhibiting a lower bound of 2 − 1 m for the scheduling problem with unrelated machines (formulated as a mechanism design problem in the seminal paper of Nisan and Ronen on Algorithmic Mechanism Design). Our lower bound applies to truthful randomized mechanisms (disregarding any computational assumptions on the running time of these mechanisms). Moreover, it holds even for the weaker notion of truthfulness for randomized mech-anisms – i.e., truthfulness in expectation. This lower bound nearly matches the known 7 4 (randomized) truthful upper bound for the case of two machines (a non-truthful FPTAS exists). No lower bound for truthful randomized mechanisms in multi-parameter settings was previously known. We show an application of our techniques to the workload-minimization problem in networks. We prove our lower bounds for this problem in the inter-domain routing setting presented by Feigenbaum, Papadimitriou, Sami, and Shenker. Finally, we discuss several notions of non-utilitarian “fairness ” (Max-Min fairness, Min-Max fairness, and envy minimization). We show how our techniques can be used to prove lower bounds for these notions.