AF: Small: Problems in Algorithmic Game Theory for Online Markets

25年前，互联网的出现改变了理论计算机科学的研究。这种新的和关键的计算人工制品需要为其研究提供新的数学建模、思想和技术武器库。由于市场和激励在新的计算环境的功能和演变中扮演着重要的角色，博弈论和微观经济学的计算分支最终在互联网的启发下发展起来。这个被称为算法博弈论的新领域将算法思维与经济考量结合在一起，并对当今复杂的计算环境产生了至关重要的见解，包括互联网和人工智能(AI)。这个项目的目标是解决近年来出现的算法博弈论中的新一代开放问题。这项研究的结果可能会产生从理论计算机科学到经济学和博弈论以及机器学习的影响。本项目将探索的研究方向包括：(1)基于博弈的动力学，开发与博弈的新应用更相关、更有利于计算的新的解概念；以及解决关于博弈和市场中的均衡的一些基本开放问题的复杂性。(2)调查在线市场和平台中的新配方和问题，以及解决与在匹配市场中实现各种均衡概念相关的某些计算问题。(3)研究与在线市场和机器学习系统中的公平和不公平有关的某些新问题。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

A quarter of a century ago, research in Theoretical Computer Science was transformed by the advent of the Internet. This new and crucial computational artifact requires for its study a new arsenal of mathematical modeling, ideas and techniques. Since markets and incentives play an important role in the function and evolution of the new computational environment, computational branches of Game Theory and Microeconomics were eventually developed, inspired by the Internet. The new field thus created, dubbed Algorithmic Game Theory, combined algorithmic thinking with economic considerations, and has produced crucial insights into today's complex computational environment, which encompasses both the Internet and artificial intelligence (AI). The goal of this project is to address a new generation of open questions in Algorithmic Game Theory that have emerged in recent years. Results from this research are likely to have an impact beyond Theoretical Computer Science to Economics and Game Theory, as well as Machine Learning. The research directions that will be explored in this project include the following: (1) Develop new solution concepts that are more pertinent to the new applications of games and more friendly to computation, based on the dynamics of games; and address the complexity of some basic open questions regarding equilibria in games and markets. (2) Investigate novel formulations and problems in on-line markets and platforms, as well as address certain computational problems related to achieving various notions of equilibrium in matching markets. (3) Study certain novel problems related to fairness and inequity in online markets and machine learning systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.