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Bayesian algorithmic mechanism design

Bayesian algorithmic mechanism design Bayesian Algorithmic Mechanism Design SHUCHI CHAWLA University of Wisconsin - Madison and BALASUBRAMANIAN SIVAN Microsoft Research This article surveys recent work with an algorithmic flavor in Bayesian mechanism design. Bayesian mechanism design involves optimization in economic settings where the designer possesses some stochastic information about the input. Recent years have witnessed huge advances in our knowledge and understanding of algorithmic techniques for Bayesian mechanism design problems. These include, for example, revenue maximization in settings where buyers have multi-dimensional preferences, optimization of non-linear objectives such as makespan, and generic reductions from mechanism design to algorithm design. However, a number of tantalizing questions remain unsolved. This article is meant to serve as an introduction to Bayesian mechanism design for a novice, as well as a starting point for a broader literature search for an experienced researcher. Categories and Subject Descriptors: J.4 [Social and Behavioral Sciences]: Economics General Terms: Algorithms; Economics; Theory Additional Key Words and Phrases: mechanism design, auctions, optimization, approximation, Bayes-Nash equilibrium 1. INTRODUCTION Mechanism design deals with optimization in strategic settings. The mechanism designer's task is to design a system involving strategic participants, a.k.a. agents, who act in their own self-interest. The system should be designed in a http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM SIGecom Exchanges Association for Computing Machinery

Bayesian algorithmic mechanism design

Chawla, Shuchi; Sivan, Balasubramanian
ACM SIGecom Exchanges , Volume 13 (1) – Nov 25, 2014
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Publisher
Association for Computing Machinery
Copyright
Copyright © 2014 by ACM Inc.
ISSN
1551-9031
DOI
10.1145/2692375.2692378
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Abstract

Bayesian Algorithmic Mechanism Design SHUCHI CHAWLA University of Wisconsin - Madison and BALASUBRAMANIAN SIVAN Microsoft Research This article surveys recent work with an algorithmic flavor in Bayesian mechanism design. Bayesian mechanism design involves optimization in economic settings where the designer possesses some stochastic information about the input. Recent years have witnessed huge advances in our knowledge and understanding of algorithmic techniques for Bayesian mechanism design problems. These include, for example, revenue maximization in settings where buyers have multi-dimensional preferences, optimization of non-linear objectives such as makespan, and generic reductions from mechanism design to algorithm design. However, a number of tantalizing questions remain unsolved. This article is meant to serve as an introduction to Bayesian mechanism design for a novice, as well as a starting point for a broader literature search for an experienced researcher. Categories and Subject Descriptors: J.4 [Social and Behavioral Sciences]: Economics General Terms: Algorithms; Economics; Theory Additional Key Words and Phrases: mechanism design, auctions, optimization, approximation, Bayes-Nash equilibrium 1. INTRODUCTION Mechanism design deals with optimization in strategic settings. The mechanism designer's task is to design a system involving strategic participants, a.k.a. agents, who act in their own self-interest. The system should be designed in a

Journal

ACM SIGecom Exchanges – Association for Computing Machinery

Published: Nov 25, 2014

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