CAREER: Incentives, Fairness, and Efficiency without Monetary Transfers

职业：激励、公平和效率，无需货币转移

基本信息

批准号：
2144208
负责人：
Christos Psomas
金额：
$ 59.14万
依托单位：
Purdue University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-07-01 至 2027-06-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2144208&HistoricalAwards=false
关键词：
CAREER Incentives Fairness Efficiency without

项目摘要

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).The Internet and the vast increase in the availability of data have transformed algorithm design, as well as computer science in general. From computational resources and advertising space, to food donations, loans, kidneys, and vaccines, algorithms are increasingly being used to decide how scarce resources are allocated. As opposed to traditional optimization, the input to these algorithms must be solicited from strategic agents, with their own, private preferences over the algorithm's output. And, from resource allocation in the cloud and spectrum auctions to tournaments in major sporting events (such as the Olympics), it is well-understood that these strategic entities will behave to optimize their own benefit to the extent possible while still “following the rules,” leading to unpredictable final outcomes. At the same time, unlike traditional optimization, in many of these modern applications, system designers must also consider whether their system is equitable among its participants. Classic work in Economics, as well as extensive work in the intersection of Computer Science and Economics, provides a rich toolkit for designing algorithms that are immune to strategic manipulations as well as algorithms that balance fairness and efficiency. This project aims to advance and develop this theory with a focus on domains where monetary transfers are not allowed, by taking aim at several fundamental open questions. The project also contains plans to design, develop, and deploy a system that is based on the proposed theoretical research and that serves the local community by enabling local non-profit organizations that fight hunger to allocate their food donations in a more efficient manner.The project will expand the reach of theory into areas where there is a major gap in current understanding, by taking aim at several key theoretical questions in the following three complementary thrusts. (1) Foundations of mechanism design without money. The project takes aim at fundamental questions in this space, with the goal of developing tools for designing truthful mechanisms for a number of paradigms: divisible and indivisible goods, static and dynamic environments, worst-case and Bayesian objectives. (2) Mechanism design with imperfect rationality. There are important domains in which protecting against fully rational, expected utility-maximizing participants is overly cautious. This project puts forward and explores several possibilities for modeling imperfect rationality. (3) Mechanism design with imperfect expressivity. Eliciting complex utility functions is often infeasible, e.g., because of agents' cognitive limitations. The project explores the trade-off between expressiveness and ease of elicitation in mechanism design without money.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.

该奖项的全部或部分资金来源于《2021 年美国救援计划法案》（公法 117-2）。互联网和数据可用性的大幅增加已经改变了算法设计以及整个计算机科学。从计算资源和广告空间，到食品捐赠、贷款、肾脏和疫苗，算法越来越多地被用来决定如何分配稀缺资源。与传统的优化相反，这些算法的输入必须从战略代理那里征求他们的意见。自己的个人偏好而且，从云中的资源分配和频谱拍卖到重大体育赛事（例如奥运会）的锦标赛，众所周知，这些战略实体将在“尽可能优化自身利益”的情况下采取行动。同时，与传统的优化不同，在许多现代应用中，系统设计者还必须考虑他们的系统在经济学的参与者之间是否公平。在计算机科学和计算机科学的交叉领域工作经济学提供了一个丰富的工具包，用于设计不受战略操纵的算法以及平衡公平和效率的算法。该项目旨在通过瞄准不允许货币转移的领域来推进和发展这一理论。该项目还包含设计、开发和部署一个系统的计划，该系统基于拟议的理论研究，并通过使当地抗击饥饿的非营利组织能够按比例分配其食物捐赠来为当地社区服务。更有效的方式。该项目将扩大理论的范围通过针对以下三个补充主旨中的几个关键理论问题，深入了解当前理解存在重大差距的领域：（1）无资金机制设计的基础该项目针对该领域的基本问题。 (2)不完全理性的机制设计存在着一些重要的领域，需要防范完全理性的、预期的。效用最大化的参与者过于谨慎。该项目提出并探索了对不完美理性进行建模的几种可能性。（3）由于代理人的认知限制，引出复杂的效用函数通常是不可行的。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Leakage Inversion: Towards Quantifying Privacy in Searchable Encryption

泄漏反演：量化可搜索加密中的隐私

DOI：
10.1145/3548606.3560593
发表时间：
2022
期刊：
SIGSAC Conference on Computer and Communications Security
影响因子：
0
作者：
Kornaropoulos, Evgenios M.;Moyer, Nathaniel;Papamanthou, Charalampos;Psomas, Alexandros
通讯作者：
Psomas, Alexandros

On Hiring Secretaries with Stochastic Departures

论雇用随机离职的秘书

DOI：
10.1287/opre.2023.2476
发表时间：
2023
期刊：
Operations Research
影响因子：
2.7
作者：
Kesselheim, Thomas;Psomas, Alexandros;Vardi, Shai
通讯作者：
Vardi, Shai

Dynamic Fair Division with Partial Information

具有部分信息的动态公平划分

DOI：
发表时间：
2022
期刊：
Advances in neural information processing systems
影响因子：
0
作者：
Benade, Gerdus;Halpern, Daniel;Psomas, Alexandros
通讯作者：
Psomas, Alexandros

Simple Mechanisms for Welfare Maximization in Rich Advertising Auctions

丰富的广告拍卖中实现福利最大化的简单机制

DOI：
发表时间：
2022
期刊：
Advances in neural information processing systems
影响因子：
0
作者：
Aggarwal, Gagan;Bhawalkar, Kshipra;Mehta, Aranyak;Mohan, Divyarthi;Psomas, Alexandros
通讯作者：
Psomas, Alexandros

Fair and Efficient Allocations Without Obvious Manipulations

公平高效的分配，没有明显的操纵