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Approximately optimal mechanism design: motivation, examples, and lessons learned

Approximately optimal mechanism design: motivation, examples, and lessons learned Approximately Optimal Mechanism Design: Motivation, Examples, and Lessons Learned TIM ROUGHGARDEN Stanford University This survey describes the approximately optimal mechanism design paradigm and uses it to investigate two basic questions in auction theory. First, when is complexity -- in the sense of detailed distributional knowledge -- an essential feature of revenue-maximizing single-item auctions? Second, do combinatorial auctions require high-dimensional bid spaces to achieve good social welfare? Categories and Subject Descriptors: F.0 [Theory of Computation]: General General Terms: Algorithms, Economics, Theory Additional Key Words and Phrases: Mechanism design, auctions, approximation 1. INTRODUCTION 1.1 Preamble Optimal mechanism design enjoys a beautiful and well-developed theory, and also a number of killer applications. Rules of thumb produced by the field influence everything from how governments sell wireless spectrum licenses to how the major search engines auction off online advertising. There are, however, some basic problems for which the traditional optimal mechanism design approach is ill-suited -- either because it makes overly strong assumptions, or because it advocates overly complex designs. The thesis of this survey is that approximately optimal mechanisms allow us to reason about fundamental questions that seem out of reach of the traditional theory. 1.2 Organization This survey has three http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGecom Exchanges Association for Computing Machinery

Approximately optimal mechanism design: motivation, examples, and lessons learned

ACM SIGecom Exchanges , Volume 13 (2) – Jan 28, 2015

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2015 by ACM Inc.
ISSN
1551-9031
DOI
10.1145/2728732.2728733
Publisher site
See Article on Publisher Site

Abstract

Approximately Optimal Mechanism Design: Motivation, Examples, and Lessons Learned TIM ROUGHGARDEN Stanford University This survey describes the approximately optimal mechanism design paradigm and uses it to investigate two basic questions in auction theory. First, when is complexity -- in the sense of detailed distributional knowledge -- an essential feature of revenue-maximizing single-item auctions? Second, do combinatorial auctions require high-dimensional bid spaces to achieve good social welfare? Categories and Subject Descriptors: F.0 [Theory of Computation]: General General Terms: Algorithms, Economics, Theory Additional Key Words and Phrases: Mechanism design, auctions, approximation 1. INTRODUCTION 1.1 Preamble Optimal mechanism design enjoys a beautiful and well-developed theory, and also a number of killer applications. Rules of thumb produced by the field influence everything from how governments sell wireless spectrum licenses to how the major search engines auction off online advertising. There are, however, some basic problems for which the traditional optimal mechanism design approach is ill-suited -- either because it makes overly strong assumptions, or because it advocates overly complex designs. The thesis of this survey is that approximately optimal mechanisms allow us to reason about fundamental questions that seem out of reach of the traditional theory. 1.2 Organization This survey has three

Journal

ACM SIGecom ExchangesAssociation for Computing Machinery

Published: Jan 28, 2015

References