VC v. VCG: Inapproximability of Combinatorial Auctions via Generalizations of the VC Dimension

The existence of incentive-compatible computationally-efficient protocols for combinatorial auctions with decent approximation ratios is the paradigmatic problem in computational mechanism design. It is believed that in many cases good approximations for combinatorial auctions may be unattainable due to an inherent clash between truthfulness and computational efficiency. However, to date, researchers lack the machinery to prove such results. In this paper, we present a new approach that we believe holds great promise for making progress on this important problem. We take the first steps towards the development of new technologies for lower bounding the VC-dimension of k-tuples of disjoint sets. We apply this machinery to prove the first computational-complexity inapproximability results for incentive-compatible mechanisms for combinatorial auctions. These results hold for the important class of VCG-based mechanisms, and are based on the complexity assumption that NP has no polynomial-size circuits. Statistics and Computer Science, U.C. Berkeley, and Mathematics and Computer Science Weizmann Institute. Supported by Sloan fellowship in Mathematics, NSF Career award DMS 0548249, DOD grant N0014-07-1-05-06, and by ISF. [email protected] Computer Science Division University of California at Berkeley, CA, 94720 USA. [email protected] Department of Computer Science, Yale University, CT, USA, and Computer Science Division, University of California at Berkeley, CA, USA. Supported by NSF grant 0331548. [email protected]. Computer Science Division University of California at Berkeley, CA, 94720 USA. [email protected].