Algorithmic mechanism design (extended abstract)
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
A PCP characterization of NP with optimal amortized query complexity
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Simple analysis of graph tests for linearity and PCP
Random Structures & Algorithms
Approximation techniques for utilitarian mechanism design
Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
Mechanism Design via Machine Learning
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Truthful and Near-Optimal Mechanism Design via Linear Programming
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Single-value combinatorial auctions and implementation in undominated strategies
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Optimal approximation for the submodular welfare problem in the value oracle model
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
More efficient queries in PCPs for NP and improved approximation hardness of maximum CSP
Random Structures & Algorithms
On the Hardness of Being Truthful
FOCS '08 Proceedings of the 2008 49th Annual IEEE Symposium on Foundations of Computer Science
Near-optimal algorithms for maximum constraint satisfaction problems
ACM Transactions on Algorithms (TALG)
Bayesian algorithmic mechanism design
Proceedings of the forty-second ACM symposium on Theory of computing
Pseudorandom generators for polynomial threshold functions
Proceedings of the forty-second ACM symposium on Theory of computing
Inapproximability for VCG-based combinatorial auctions
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Bounded Independence Fools Degree-2 Threshold Functions
FOCS '10 Proceedings of the 2010 IEEE 51st Annual Symposium on Foundations of Computer Science
Black-Box Randomized Reductions in Algorithmic Mechanism Design
FOCS '10 Proceedings of the 2010 IEEE 51st Annual Symposium on Foundations of Computer Science
Single-parameter combinatorial auctions with partially public valuations
SAGT'10 Proceedings of the Third international conference on Algorithmic game theory
From convex optimization to randomized mechanisms: toward optimal combinatorial auctions
Proceedings of the forty-third annual ACM symposium on Theory of computing
Bayesian incentive compatibility via fractional assignments
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Bayesian incentive compatibility via matchings
Proceedings of the twenty-second annual ACM-SIAM symposium on Discrete Algorithms
Black-box reductions for cost-sharing mechanism design
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
On the limits of black-box reductions in mechanism design
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
| Hi-index | 0.00 |
A central question in algorithmic mechanism design is to understand the additional difficulty introduced by truthfulness requirements in the design of approximation algorithms for social welfare maximization. In this paper, by studying the problem of single-parameter combinatorial auctions, we obtain the first black-box reduction that converts any approximation algorithm to a truthful mechanism with essentially the same approximation factor in a prior-free setting. In fact, our reduction works for the more general class of symmetric single-parameter problems. Here, a problem is symmetric if its allocation space is closed under permutations. As extensions, we also take an initial step towards exploring the power of black-box reductions for general single-parameter and multi-parameter problems by showing several positive and negative results. We believe that the algorithmic and game theoretic insights gained from our approach will help better understand the tradeoff between approximability and the incentive compatibility.