48,634 research outputs found
Possible Winners in Noisy Elections
We consider the problem of predicting winners in elections, for the case
where we are given complete knowledge about all possible candidates, all
possible voters (together with their preferences), but where it is uncertain
either which candidates exactly register for the election or which voters cast
their votes. Under reasonable assumptions, our problems reduce to counting
variants of election control problems. We either give polynomial-time
algorithms or prove #P-completeness results for counting variants of control by
adding/deleting candidates/voters for Plurality, k-Approval, Approval,
Condorcet, and Maximin voting rules. We consider both the general case, where
voters' preferences are unrestricted, and the case where voters' preferences
are single-peaked.Comment: 34 page
Heuristics in Multi-Winner Approval Voting
In many real world situations, collective decisions are made using voting.
Moreover, scenarios such as committee or board elections require voting rules
that return multiple winners. In multi-winner approval voting (AV), an agent
may vote for as many candidates as they wish. Winners are chosen by tallying up
the votes and choosing the top- candidates receiving the most votes. An
agent may manipulate the vote to achieve a better outcome by voting in a way
that does not reflect their true preferences. In complex and uncertain
situations, agents may use heuristics to strategize, instead of incurring the
additional effort required to compute the manipulation which most favors them.
In this paper, we examine voting behavior in multi-winner approval voting
scenarios with complete information. We show that people generally manipulate
their vote to obtain a better outcome, but often do not identify the optimal
manipulation. Instead, voters tend to prioritize the candidates with the
highest utilities. Using simulations, we demonstrate the effectiveness of these
heuristics in situations where agents only have access to partial information
Approval-Based Shortlisting
Shortlisting is the task of reducing a long list of alternatives to a
(smaller) set of best or most suitable alternatives from which a final winner
will be chosen. Shortlisting is often used in the nomination process of awards
or in recommender systems to display featured objects. In this paper, we
analyze shortlisting methods that are based on approval data, a common type of
preferences. Furthermore, we assume that the size of the shortlist, i.e., the
number of best or most suitable alternatives, is not fixed but determined by
the shortlisting method. We axiomatically analyze established and new
shortlisting methods and complement this analysis with an experimental
evaluation based on biased voters and noisy quality estimates. Our results lead
to recommendations which shortlisting methods to use, depending on the desired
properties
Computational Aspects of Multi-Winner Approval Voting
We study computational aspects of three prominent voting rules that use
approval ballots to elect multiple winners. These rules are satisfaction
approval voting, proportional approval voting, and reweighted approval voting.
We first show that computing the winner for proportional approval voting is
NP-hard, closing a long standing open problem. As none of the rules are
strategyproof, even for dichotomous preferences, we study various strategic
aspects of the rules. In particular, we examine the computational complexity of
computing a best response for both a single agent and a group of agents. In
many settings, we show that it is NP-hard for an agent or agents to compute how
best to vote given a fixed set of approval ballots from the other agents
Complexity of Manipulation, Bribery, and Campaign Management in Bucklin and Fallback Voting
A central theme in computational social choice is to study the extent to
which voting systems computationally resist manipulative attacks seeking to
influence the outcome of elections, such as manipulation (i.e., strategic
voting), control, and bribery. Bucklin and fallback voting are among the voting
systems with the broadest resistance (i.e., NP-hardness) to control attacks.
However, only little is known about their behavior regarding manipulation and
bribery attacks. We comprehensively investigate the computational resistance of
Bucklin and fallback voting for many of the common manipulation and bribery
scenarios; we also complement our discussion by considering several campaign
management problems for Bucklin and fallback.Comment: 28 page
How Hard Is It to Control an Election by Breaking Ties?
We study the computational complexity of controlling the result of an
election by breaking ties strategically. This problem is equivalent to the
problem of deciding the winner of an election under parallel universes
tie-breaking. When the chair of the election is only asked to break ties to
choose between one of the co-winners, the problem is trivially easy. However,
in multi-round elections, we prove that it can be NP-hard for the chair to
compute how to break ties to ensure a given result. Additionally, we show that
the form of the tie-breaking function can increase the opportunities for
control. Indeed, we prove that it can be NP-hard to control an election by
breaking ties even with a two-stage voting rule.Comment: Revised and expanded version including longer proofs and additional
result
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