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Efficiently Characterizing Games Consistent with Perturbed Equilibrium Observations

Citation

Ziani, Juba (2017) Efficiently Characterizing Games Consistent with Perturbed Equilibrium Observations. Master's thesis, California Institute of Technology. doi:10.7907/Z91Z42CF. http://resolver.caltech.edu/CaltechTHESIS:12122016-183248666

Abstract

In this thesis, we study the problem of characterizing the set of games that are consistent with observed equilibrium play, a fundamental problem in econometrics. Our contribution is to develop and analyze a new methodology based on convex optimization to address this problem, for many classes of games and observation models of interest. Our approach provides a sharp, computationally efficient characterization of the extent to which a particular set of observations constrains the space of games that could have generated them. This allows us to solve a number of variants of this problem as well as to quantify the power of games from particular classes (e.g., zero-sum, potential, linearly parameterized) to explain player behavior.

We illustrate our approach with numerical simulations.

Item Type:Thesis (Master's thesis)
Subject Keywords:econometrics, inverse game theory, characterizing games, convex optimization, computational efficiency
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Computer Science
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Ligett, Katrina A. (advisor)
  • Chandrasekaran, Venkat (advisor)
Thesis Committee:
  • None, None
Defense Date:13 December 2016
Record Number:CaltechTHESIS:12122016-183248666
Persistent URL:http://resolver.caltech.edu/CaltechTHESIS:12122016-183248666
DOI:10.7907/Z91Z42CF
Related URLs:
URLURL TypeDescription
https://arxiv.org/abs/1603.01318arXivArticle adapted and extended for the thesis
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:9993
Collection:CaltechTHESIS
Deposited By: Juba Ziani
Deposited On:06 Jan 2017 18:09
Last Modified:26 Jan 2017 18:19

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