Title: Distance-ratioanalizability of voting rules

Speaker: Edith Elkind, NTU

Time/Date: Wed, Nov 2, 2:00pm - 3:00pm
Location: Room 3405

Abstract:

A voting rule is an algorithm for determining the winner in
an election, and there are several approaches that have been used to
justify the proposed rules. One justification is to show that a rule
satisfies a set of desirable axioms that uniquely identify it. Another
is to show that the calculation that it performs can be interpreted as
maximum likelihood estimation relative to a certain model of noise
that affects the voters (MLE approach). The third approach, which has
been recently actively investigated, is the so-called distance
rationalizability framework. In it, a voting rule is defined via a
class of consensus elections (i.e., a class of elections that have a
clear winner) and a distance function. A candidate c is a winner of an
election E if c wins in one of the consensus elections that are
closest to E relative to the given distance.

In this talk, we will formally introduce the
distance-rationalizability framework and show that many well-known
voting rules can be rationalized via natural distances and
consensuses. We then explore the limitations and variants of this
approach, and relate it to the other two approaches for explaining the
voting rules, i.e., the axiomatic framework and the MLE framework.

Based on joint work with Piotr Faliszewski and Arkadii Slinko