1,982 research outputs found
Efficient Algorithms for Envy-Free Stick Division With Fewest Cuts
Given a set of n sticks of various (not necessarily different) lengths, what
is the largest length so that we can cut k equally long pieces of this length
from the given set of sticks? We analyze the structure of this problem and show
that it essentially reduces to a single call of a selection algorithm; we thus
obtain an optimal linear-time algorithm.
This algorithm also solves the related envy-free stick-division problem,
which Segal-Halevi, Hassidim, and Aumann (AAMAS, 2015) recently used as their
central primitive operation for the first discrete and bounded envy-free cake
cutting protocol with a proportionality guarantee when pieces can be put to
waste.Comment: v3 adds more context about the proble
Multiwinner Voting with Fairness Constraints
Multiwinner voting rules are used to select a small representative subset of
candidates or items from a larger set given the preferences of voters. However,
if candidates have sensitive attributes such as gender or ethnicity (when
selecting a committee), or specified types such as political leaning (when
selecting a subset of news items), an algorithm that chooses a subset by
optimizing a multiwinner voting rule may be unbalanced in its selection -- it
may under or over represent a particular gender or political orientation in the
examples above. We introduce an algorithmic framework for multiwinner voting
problems when there is an additional requirement that the selected subset
should be "fair" with respect to a given set of attributes. Our framework
provides the flexibility to (1) specify fairness with respect to multiple,
non-disjoint attributes (e.g., ethnicity and gender) and (2) specify a score
function. We study the computational complexity of this constrained multiwinner
voting problem for monotone and submodular score functions and present several
approximation algorithms and matching hardness of approximation results for
various attribute group structure and types of score functions. We also present
simulations that suggest that adding fairness constraints may not affect the
scores significantly when compared to the unconstrained case.Comment: The conference version of this paper appears in IJCAI-ECAI 201
Multiwinner Elections with Diversity Constraints
We develop a model of multiwinner elections that combines performance-based
measures of the quality of the committee (such as, e.g., Borda scores of the
committee members) with diversity constraints. Specifically, we assume that the
candidates have certain attributes (such as being a male or a female, being
junior or senior, etc.) and the goal is to elect a committee that, on the one
hand, has as high a score regarding a given performance measure, but that, on
the other hand, meets certain requirements (e.g., of the form "at least
of the committee members are junior candidates and at least are
females"). We analyze the computational complexity of computing winning
committees in this model, obtaining polynomial-time algorithms (exact and
approximate) and NP-hardness results. We focus on several natural classes of
voting rules and diversity constraints.Comment: A short version of this paper appears in the proceedings of AAAI-1
Multi-Winner Voting with Approval Preferences
Approval-based committee (ABC) rules are voting rules that output a
fixed-size subset of candidates, a so-called committee. ABC rules select
committees based on dichotomous preferences, i.e., a voter either approves or
disapproves a candidate. This simple type of preferences makes ABC rules widely
suitable for practical use. In this book, we summarize the current
understanding of ABC rules from the viewpoint of computational social choice.
The main focus is on axiomatic analysis, algorithmic results, and relevant
applications.Comment: This is a draft of the upcoming book "Multi-Winner Voting with
Approval Preferences
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