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，基础设施安全、器官交换、广告拍卖和居民匹配的算法在全球范围内被采用。我的研究重点放在基本的解决方案概念上，这些概念定义广泛，分析上也很优雅，因为这样的解决方案很容易理解，因此有可能在实践中快速采用。我有兴趣分析它们在实际应用中的优势和劣势。*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-计算公平划分领域的中心问题，应用包括继承划分和离婚解决方案，并表明简单地最大化纳什福利(公用事业的乘积)会产生文献中任何其他已知解决方案概念都不提供的令人信服的公平和效率保证。同样，在最近的另一项工作中，我们研究了一种不同的原则解概念，即最大化最小效用的leximin机制。众所周知，它非常适合在集群中公平分配计算资源，但我们证明了它的公平性、效率和博弈论性质扩展到了更广泛的领域，包括了以前从10多篇文献中研究的现实世界设置。*我认为这些想法有可能适用于更广泛的现实世界问题领域。例如，MNW解决方案可能有助于在室友之间分配房间，通过将金钱建模为可分商品来划分租金，并限制分配空间，以便每个室友获得一个房间。我认为，福利最大化也可以应用于遥远的投票理论领域，在投票理论中，典型的做法是不向选民索要公用事业，而是对替代方案进行有序比较。我们最近发现，以序数信息为目标的福利的最佳逼近在实际数据上表现得很好。但这种方法的理论保证还需要进一步研究。*我的工作导致了两个非营利性网站的开发，RoboVote.org和Spliddit.org，这两个网站在投票和公平分配方面实施基本解决方案，以解决现实世界的问题。这些网站在三年内吸引了超过10万用户，这表明此类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.