2010 IEEE 51st Annual Symposium on Foundations of Computer Science (2010)
Las Vegas, Nevada USA
Oct. 23, 2010 to Oct. 26, 2010
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/FOCS.2010.79
We give the first black-box reduction from arbitrary approximation algorithms to truthful approximation mechanisms for a non-trivial class of multi-parameter problems. Specifically, we prove that every packing problem that admits an FPTAS also admits a truthful-in-expectation randomized mechanism that is an FPTAS. Our reduction makes novel use of smoothed analysis, by employing small perturbations as a tool in algorithmic mechanism design. We develop a “duality'' between linear perturbations of the objective function of an optimization problem and of its feasible set, and use the “primal'' and “dual'' viewpoints to prove the running time bound and the truthfulness guarantee, respectively, for our mechanism.
Mechanism Design, Truthful Approximation Algorithms, Smoothed Analysis
T. Roughgarden and S. Dughmi, "Black-Box Randomized Reductions in Algorithmic Mechanism Design," 2010 IEEE 51st Annual Symposium on Foundations of Computer Science(FOCS), Las Vegas, Nevada USA, 2010, pp. 775-784.