Prior-Free Mechanisms with Welfare Estimates

Guru Guruganesh, Jon Schneider, Joshua Ruizhi Wang

Keywords: prior-free distributions, mechanism design, digital goods

TL;DR: We consider the problem of designing prior-free mechanisms for allocating items to buyers when the mechanism is additionally provided with an estimate for the optimal welfare .

Abstract: We consider the problem of designing prior-free revenue-maximizing mechanisms for allocating items to $n$ buyers when the mechanism is additionally provided with an estimate for the optimal welfare (which is guaranteed to be correct to within a multiplicative factor of $1/\alpha$). In the digital goods setting (where we can allocate items to an arbitrary subset of the buyers), we demonstrate a mechanism which achieves revenue that is $O(\log n/\alpha)$-competitive with the optimal welfare. In the public goods setting (where we either must allocate the item to all buyers or to no buyers), we demonstrate a mechanism which is $O(n\log 1/\alpha)$ competitive. In both settings, we show the dependence on $\alpha$ and $n$ is tight. Finally, we discuss generalizations to broader classes of allocation constraints.

Track: Economics, Online Markets, and Human Computation

Submission Guidelines Scope: Yes

Submission Guidelines Blind: Yes

Submission Guidelines Format: Yes

Submission Guidelines Limit: Yes

Submission Guidelines Authorship: Yes

Student Author: No

Submission Number: 1143