Tutorial: Computational Social Choice

Tutorial on Computational Social Choice

Speakers: Haris Aziz and Nicholas Mattei

Slides Part 1

Slides Part 2


Social choice theory is the study of representation and aggregation of individual preferences. In recent years, the study of computational social choice has bloomed and been applied in many areas including recommender systems and kidney exchanges. Two key domains within social choice theory are voting, the foundation of many group decision-making and recommendation processes; and resource allocation, for computational resources as well as allocating airport runways and radio spectra.

In this tutorial, we will give an introduction and overview of classic results pertaining to voting. Starting from the fundamentals of voting and Arrow’s Impossibility theorem we will cover popular voting mechanisms, their axiomatic properties, usefulness in collective decision making, and their computational aspects.

We will then cover fundamentals of matching, allocation, and exchange of resources. The tutorial will cover several topics including fair allocation of divisible and indivisible goods as well as axiomatic properties of well-known mechanisms. Finally, we will highlight some recent developments in the field of computational social choice and offer suggestions for interested researchers to join this exciting field.

This tutorial is intended for the general AI community and we assume no prior knowledge about computational social choice.

Haris Aziz

Haris Aziz is a research scientist in the optimization group at NICTA and is a conjoint lecturer at the University of New South Wales. His research interests lie at the intersection of economics and computer science---especially algorithmic game theory and computational social choice. He was based at the University of Oxford and University of Warwick for his higher studies and LMU Munchen and Technische Universitat Munchen for his postdoctoral research. Haris has published at economics and computer science venues such as Games and Economic Behavior, Mathematical Social Sciences, Economics Letters, Artificial Intelligence, Journal of Artificial Intelligence Research, Operations Research Letters, AAAI, AAMAS, ACM EC, IJCAI, SAGT, STACS and WINE. He has served as a Program Committee /Senior Program Committee member of conferences including ACM EC, AAAI, AAMAS, IJCAI and COMSOC and was the co-chair of CoopMAS 2013.


Nicholas Mattei

Nicholas Mattei is a research scientist in the Optimization Research Group at NICTA and a conjoint lecturer at the University of New South Wales in Sydney, Australia. His research focuses on computational aspects of social choice, preference aggregation, and assignment --- how computers can enable and augment human decision making. His current interest lies in finding and demonstrating practical applications of many of the concepts in social choice and decision theory. A main thrust of this recent work has been, along with Toby Walsh, the foundation and maintenance of PrefLib: A Library for Preferences. He previously worked as a programmer and embedded electronics designer for nano-satellites at NASA Ames Research Center. He received his Ph.D from the University of Kentucky under the supervision of Dr. Judy Goldsmith. He has served on the Program Committee of IJCAI and AAAI and was the co-chair for the 1st Workshop on Exploring Beyond the Worst Case in Computational Social Choice (EXPLORE 2014).