Using Fundamental Economic Solutions to Solve Real-World Problems

最近，计算机科学和经济学之间的联盟对基础设施安全、器官交换、广告拍卖和居民匹配的算法产生了巨大的社会影响。我的研究重点是基本的解决方案概念，这些解决方案定义广泛，分析优雅，因为这样的解决方案易于理解，因此在实践中具有快速采用的潜力。我感兴趣的是分析它们在实际应用中的优缺点。******例如，在我最近与合作者的合作中，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核心问题，其应用包括继承分配和离婚解决，并表明仅仅最大化纳什福利（效用产品）会产生令人信服的公平和效率保证，这是文献中任何其他已知解决方案概念都无法提供的。同样，在最近的另一项工作中，我们研究了一个不同的原则性解决概念，即leximin机制，它使最小效用最大化。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，包括以前研究过的10多篇文献中的现实世界设置。******我认为，这些想法有可能适用于更广泛的现实问题领域。例如，MNW解决方案可能有助于在室友之间分配房间，并通过将金钱建模为可分割的商品来划分租金，并限制分配空间，以便每个室友都能分到一个房间。我认为，福利最大化也可以应用于遥远的投票理论领域，在这个领域，典型的做法是不向选民询问效用，而是对备选方案进行顺序比较。我们最近表明，以有序信息为目标的福利的最佳近似在实际数据上表现良好。但是这种方法的理论保证需要进一步的研究。******我的工作促成了两个非营利性网站的发展，RoboVote.org和Spliddit.org，它们在投票和公平分配方面实现了基本的解决方案，以解决现实世界的问题。这些网站在三年内吸引了超过10万名用户，这表明这些解决方案有潜力帮助整个社会。

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.