DS-2021-11: Strategyproof Social Choice for Restricted Domains

DS-2021-11: Botan, Sirin (2021) Strategyproof Social Choice for Restricted Domains. Doctoral thesis, University of Amsterdam.

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Abstract

This thesis examines strategic manipulation in three areas of social choice theory - single-winner voting, multiwinner voting, and judgment aggregation. It is widely accepted that strategyproofness often does not play nice with other axioms. While we would like our aggregation methods to be strategyproof - meaning no agent has an incentive to misreport her preferences or opinions - strategic manipulation is difficult to avoid, no matter what specific framework we consider.

A well-known and often used approach is to consider only specific types of input to the aggregation method - so-called restricted domains. Our approach here is to consider manipulation on profiles that fall within certain restricted domains where existing results tell us manipulation within the domain is not possible. In general we ask whether agents can manipulate from a profile in a ``well-behaved'' domain to one outside the domain in question.

By showing that an aggregation method is strategyproof in this sense, we show that allowing all inputs will not create unnecessary possibilities for manipulation. Thus, our work is an argument against restricting the domain of the aggregation method. We also aim to understand how strategyproofness on these domains can interact with the axiomatic properties of our aggregation methods.

Chapters 3, 4, and 5 each focus on this larger question in a different framework within the area of social choice. In each chapter we focus on a particular domain, and a particular class of aggregation methods. Chapter 3 looks at (single-winner) voting, focusing on the domain of profiles with a Condorcet winner. Chapter 4 considers approval-based multiwinner voting, where we study strategyproofness on party-list profiles, where any two approval sets either coincide or are disjoint. Chapter 5 discusses strategyproofness of \emph{majoritarian} judgment aggregation rules on profiles with a consistent majority.

Item Type:	Thesis (Doctoral)
Report Nr:	DS-2021-11
Series Name:	ILLC Dissertation (DS) Series
Year:	2021
Depositing User:	Dr Marco Vervoort
Date Deposited:	14 Jun 2022 15:17
Last Modified:	14 Jun 2022 15:17
URI:	https://eprints.illc.uva.nl/id/eprint/2197

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