# Overview

In empirical game theoretic analysis (EGTA), the goal is to analyze or estimate various properties of a game, given only noisy blackbox (simulator) access to it.In particular, this means that we do not know the
*utility function* of the game, and can only access samples of (per-player) utility values at any strategy profile (configuration of all player strategies) that,
*in expectation*, match the utility of said profile.

Over the last several years, alongside my collaborators Amy Greenwald, and Enrique Areyan Viqueira, I have worked to bound the sample complexity of estimating equilibria and other properties of games in this setting. Furthermore, we have extended these ideas to
*mechanism design*, wherein the goal is not just to estimate the properties of a game, but to modify a game or select its parameters in order to incentivize various types of strategic behavior and other desiderata.