Using Fundamental Economic Solutions to Solve Real-World Problems

计算机科学和经济学之间的联盟最近产生了巨大的社会影响，在全球范围内采用了基础设施安全，器官交换，广告拍卖和居民匹配的算法。我的研究重点是基本的解决方案概念，这些概念定义广泛，分析优雅，因为这些解决方案易于理解，因此有可能在实践中快速采用。我对分析它们在实际应用中的优点和缺点很感兴趣。* 例如，在我最近与合作者的工作中，我们考虑了在个人之间公平分配一组商品的问题-计算公平分配领域的中心问题，其应用包括继承分配和离婚解决，证明了仅仅最大化纳什福利（效用的乘积）导致文献中的任何其它已知解决方案概念所不提供的令人信服的公平性和效率保证。同样，在最近的另一项工作中，我们研究了一个不同的原则解决方案的概念，leximin机制，最大限度地提高最小效用。众所周知，它非常适合在集群中公平分配计算资源，但我们表明，它的公平性，效率和博弈论属性扩展到一个更广泛的领域，包括以前研究的现实世界的设置从10多篇论文在文献中。* 我认为这些想法有可能适用于现实世界问题的更广泛领域。例如，MNW解决方案可能有助于在室友之间分配房间，并通过将货币建模为可分割的商品来分割租金，并限制分配空间，以便每个室友都得到一个房间。我认为，福利最大化也可以应用到遥远的领域的投票理论，在这是典型的不问选民的效用，而是顺序比较的替代品。最近，我们表明，目标的最佳近似福利服从有序信息表现良好的真实的数据。但这种方法的理论保证需要进一步研究。我的工作导致了两个非营利网站的发展，RoboVote.org和Spliddit.org，这两个网站实现了投票和公平分配的基本解决方案，以解决现实世界的问题。这些网站在三年内吸引了100 000多名用户，这表明这些解决方案具有帮助整个社会的潜力。

The alliance between computer science and economics has recently been making tremendous societal impact with algorithms for infrastructure security, organ exchange, ad auctions, and resident matching adopted worldwide. My research focuses on fundamental solution concepts that are broadly defined and analytically elegant as such solutions are easy to understand, and thus have potential for quick adoption in practice. I am interested in analyzing their strengths and weaknesses in practical applications. ******For example, in my recent work with collaborators, we consider the problem of fairly dividing a set of goods among individuals --- the central problem in the field of computational fair division, with applications including inheritance division and divorce settlement, and show that simply maximizing the Nash welfare (product of utilities) results in a compelling fairness and efficiency guarantees not provided by any other known solution concept in the literature. Similarly, in another recent work, we study a different principled solution concept, the leximin mechanism, which maximizes the minimum utility. It is known to be perfectly suited for fairly allocating computational resources in clusters, but we show that its fairness, efficiency, and game-theoretic properties extend to a much broader domain that subsumes previously studied real-world settings from more than 10 papers in the literature. ******I argue that these ideas have the potential to be applicable to broader domains of real-world problems. For instance, the MNW solution might be useful for assigning rooms among roommates and dividing the rent by modelling money as a divisible good, and constraining the allocation space so that each roommate receives a room. I argue that welfare maximization can also be applied to the distant field of voting theory, in which it is typical to not ask the voters for utilities, but rather ordinal comparisons of alternatives. We recently show that aiming for the best approximation of welfare subject to ordinal information performs well on real data. But theoretical guarantees of such an approach requires further study.******My work has resulted in development of two not-for-profit websites, RoboVote.org and Spliddit.org, which implement fundamental solutions in voting and fair division to solve real-world problems. The websites have attracted more than 100,000 users in three years, which shows the potential that such solutions have to help society at large.