Databases Meet Computational Social Choice
Social choice underlies the equitable and efficient operation of a society. How does one aggregate preferences of individuals, arriving at a society-wide consensus? This question has been the subject of intense debate throughout history, dating as far back as ancient Greece, and, in the past two decades, has led to the development of computational social choice - an interdisciplinary area of research and practice that combines insights from mathematics, logic, economics, and computer science. One of the main foci of computational social choice are the algorithmic aspects of determining actual or potential winners in a poll or in an election. Moreover, dealing with incompleteness and uncertainty (an inherent characteristic of polling) is an important challenge confronted by computational social choice. In recent years, the data management community embarked on an investigation of preference databases, which extend traditional databases by treating preferences on a par with relational data. The main aim of this project is to develop a unifying framework that brings together preferences, rules, outcomes, contextual information, and database query languages.
Benny Kimelfeld (Associate Professor, Technion, Israel)
Phokion Kolaitis (Distinguished Professor, UCSC, USA)
Julia Stoyanovich (Assistant Professor, NYU, USA)
“Computational Social Choice Meets Databases”, Benny Kimelfeld, Phokion Kolaitis and Julia Stoyanovich. IJCAI 2018. pdf
“On the Computational Complexity of Non-dictatorial Aggregation”, Lefteris Kirousis, Phokion Kolaitis, John Livieratos. RAMICS 2018. pdf
This work is generously supported by the US National Science Foundation (NSF) and by the US-Israel Binational Science Foundation (BSF).
NSF Grant No. 1814152 “NSF-BSF: III: Small: Collaborative Research: Databases Meet Computational Social Choice”, 7/15/2018 - 6/30/2021 (PI: Kolaitis)
NSF Grant No. 1813888 “NSF-BSF: III: Small: Collaborative Research: Databases Meet Computational Social Choice”, 7/15/2018 - 6/30/2021 (PI: Stoyanovich)
BSF Grant No. 2017753 “Databases Meet Computational Social Choice”, 7/15/2018 - 6/30/2021 (PI: Kimelfeld)