CAREER: A Broad Synthesis of Artificial Intelligence and Social Choice

职业：人工智能和社会选择的广泛综合

• 批准号: 1350598
• 负责人: Ariel Procaccia
• 金额: $ 54.83万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-15 至 2020-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1350598&HistoricalAwards=false
• 关键词: CAREER; Broad; Synthesis; Artificial; Intelligence

Social choice theory is the field that studies the aggregation of individual preferences toward a collective choice. While the artificial intelligence (AI) community has so far played a dominant role in the study of the computational aspects of social choice, the interaction between core AI paradigms and social choice theory has been surprisingly limited. This project is enhancing the interaction between the two fields through a synthesis of social choice with the following AI areas: (i) decision making under uncertainty, by building on models studied in AI to create new ways to model, analyze, and make decisions in environments where preferences are dynamically changing; (ii) multiagent systems, by studying settings where agents randomly vote over multiple states, and investigating the connection between normative properties and system performance; and finally (iii) machine learning, by employing insights about strategic behavior under structured preferences, developed in the social choice literature, in order to design regression learning algorithms that discourage strategic manipulation.An overarching goal of this project is to demonstrate the potential of social choice theory to AI researchers, and ultimately to establish social choice theory as a standard paradigm in AI. Equally importantly, this project is expected to increase the scope of social choice theory. Broader impacts include a new web-based voting system, which has the potential to serve and educate hundreds of thousands of users; dissemination through a new book on computational social choice; and a workshop on computational social choice, which will help set a new agenda for the field.

社会选择理论是研究个人偏好聚合到集体选择的领域。虽然人工智能（AI）界迄今为止在社会选择的计算方面的研究中发挥着主导作用，但核心人工智能范式和社会选择理论之间的相互作用却出人意料地有限。该项目通过将社会选择与以下人工智能领域相结合，增强两个领域之间的互动：(i) 不确定性下的决策，通过建立人工智能研究的模型，创建新的建模、分析和决策方法。偏好动态变化的环境； (ii) 多智能体系统，通过研究智能体随机投票多个状态的环境，并调查规范属性和系统性能之间的联系；最后（iii）机器学习，通过利用社会选择文献中开发的关于结构化偏好下的战略行为的见解，以设计阻止战略操纵的回归学习算法。该项目的总体目标是展示社会选择的潜力选择理论向人工智能研究人员提供帮助，最终将社会选择理论建立为人工智能的标准范式。同样重要的是，该项目预计将扩大社会选择理论的范围。更广泛的影响包括新的基于网络的投票系统，该系统有可能为数十万用户提供服务和教育；通过一本关于计算社会选择的新书进行传播；以及关于计算社会选择的研讨会，这将有助于为该领域制定新的议程。

项目成果

Fair Enough: Guaranteeing Approximate Maximin Shares

足够公平：保证大约最大最小份额

• DOI: 10.1145/3140756
• 发表时间: 2018-03
• 期刊: Journal of the ACM
• 影响因子: 2.5
• 作者: Kurokawa, David;Procaccia, Ariel D.;Wang, Junxing
• 通讯作者: Wang, Junxing

The Fluid Dynamic of Liquid Democracy

流动民主的流动动力

• 发表时间: 2018-01
• 期刊: WINE 2018
• 作者: Goelz, Paul;Kahng, Anson;Mackenzie, Simon;Procaccia, Ariel D.
• 通讯作者: Procaccia, Ariel D.

Statistical Foundations of Virtual Democracy

虚拟民主的统计基础

• DOI: 10.1609/aaai.v32i1.11727
• 发表时间: 2019-05-24
• 期刊: ArXiv
• 作者: Anson Kahng;Min Kyung Lee;Ritesh Noothigattu;Ariel D. Procaccia;Ale;ros Psomas;ros
• 通讯作者: ros

Leximin Allocations in the Real World

现实世界中的 Leximin 分配

• DOI: 10.1145/3274641
• 发表时间: 2018-11
• 期刊: ACM Transactions on Economics and Computation
• 影响因子: 1.2
• 作者: Kurokawa, David;Procaccia, Ariel D.;Shah, Nisarg
• 通讯作者: Shah, Nisarg

Failure-Aware Kidney Exchange

故障感知肾脏交换

• DOI: 10.1287/mnsc.2018.3026
• 发表时间: 2018-07
• 期刊: Management Science
• 影响因子: 5.4
• 作者: Dickerson, John P.;Procaccia, Ariel D.;Sandholm, Tuomas
• 通讯作者: Sandholm, Tuomas