671 research outputs found
Plurality Voting under Uncertainty
Understanding the nature of strategic voting is the holy grail of social
choice theory, where game-theory, social science and recently computational
approaches are all applied in order to model the incentives and behavior of
voters.
In a recent paper, Meir et al.[EC'14] made another step in this direction, by
suggesting a behavioral game-theoretic model for voters under uncertainty. For
a specific variation of best-response heuristics, they proved initial existence
and convergence results in the Plurality voting system.
In this paper, we extend the model in multiple directions, considering voters
with different uncertainty levels, simultaneous strategic decisions, and a more
permissive notion of best-response. We prove that a voting equilibrium exists
even in the most general case. Further, any society voting in an iterative
setting is guaranteed to converge.
We also analyze an alternative behavior where voters try to minimize their
worst-case regret. We show that the two behaviors coincide in the simple
setting of Meir et al., but not in the general case.Comment: The full version of a paper from AAAI'15 (to appear
A Local-Dominance Theory of Voting Equilibria
It is well known that no reasonable voting rule is strategyproof. Moreover,
the common Plurality rule is particularly prone to strategic behavior of the
voters and empirical studies show that people often vote strategically in
practice. Multiple game-theoretic models have been proposed to better
understand and predict such behavior and the outcomes it induces. However,
these models often make unrealistic assumptions regarding voters' behavior and
the information on which they base their vote.
We suggest a new model for strategic voting that takes into account voters'
bounded rationality, as well as their limited access to reliable information.
We introduce a simple behavioral heuristic based on \emph{local dominance},
where each voter considers a set of possible world states without assigning
probabilities to them. This set is constructed based on prospective candidates'
scores (e.g., available from an inaccurate poll). In a \emph{voting
equilibrium}, all voters vote for candidates not dominated within the set of
possible states.
We prove that these voting equilibria exist in the Plurality rule for a broad
class of local dominance relations (that is, different ways to decide which
states are possible). Furthermore, we show that in an iterative setting where
voters may repeatedly change their vote, local dominance-based dynamics quickly
converge to an equilibrium if voters start from the truthful state. Weaker
convergence guarantees in more general settings are also provided.
Using extensive simulations of strategic voting on generated and real
preference profiles, we show that convergence is fast and robust, that emerging
equilibria are consistent across various starting conditions, and that they
replicate widely known patterns of human voting behavior such as Duverger's
law. Further, strategic voting generally improves the quality of the winner
compared to truthful voting
On the convergence of iterative voting: how restrictive should restricted dynamics be?
We study convergence properties of iterative voting procedures. Such procedures are defined by a voting rule and a (restricted) iterative process, where at each step one agent can modify his vote towards a better outcome for himself. It is already known that if the iteration dynamics (the manner in which voters are allowed to modify their votes) are unrestricted, then the voting process may not converge. For most common voting rules this may be observed even under the best response dynamics limitation. It is therefore important to investigate whether and which natural restrictions on the dynamics of iterative voting procedures can guarantee convergence. To this end, we provide two general conditions on the dynamics based on iterative myopic improvements, each of which is sufficient for convergence. We then identify several classes of voting rules (including Positional Scoring Rules, Maximin, Copeland and Bucklin), along with their corresponding iterative processes, for which at least one of these conditions hold
Heuristic Voting as Ordinal Dominance Strategies
Decision making under uncertainty is a key component of many AI settings, and
in particular of voting scenarios where strategic agents are trying to reach a
joint decision. The common approach to handle uncertainty is by maximizing
expected utility, which requires a cardinal utility function as well as
detailed probabilistic information. However, often such probabilities are not
easy to estimate or apply.
To this end, we present a framework that allows "shades of gray" of
likelihood without probabilities. Specifically, we create a hierarchy of sets
of world states based on a prospective poll, with inner sets contain more
likely outcomes. This hierarchy of likelihoods allows us to define what we term
ordinally-dominated strategies. We use this approach to justify various known
voting heuristics as bounded-rational strategies.Comment: This is the full version of paper #6080 accepted to AAAI'1
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
A mixture of experts model for rank data with applications in election studies
A voting bloc is defined to be a group of voters who have similar voting
preferences. The cleavage of the Irish electorate into voting blocs is of
interest. Irish elections employ a ``single transferable vote'' electoral
system; under this system voters rank some or all of the electoral candidates
in order of preference. These rank votes provide a rich source of preference
information from which inferences about the composition of the electorate may
be drawn. Additionally, the influence of social factors or covariates on the
electorate composition is of interest. A mixture of experts model is a mixture
model in which the model parameters are functions of covariates. A mixture of
experts model for rank data is developed to provide a model-based method to
cluster Irish voters into voting blocs, to examine the influence of social
factors on this clustering and to examine the characteristic preferences of the
voting blocs. The Benter model for rank data is employed as the family of
component densities within the mixture of experts model; generalized linear
model theory is employed to model the influence of covariates on the mixing
proportions. Model fitting is achieved via a hybrid of the EM and MM
algorithms. An example of the methodology is illustrated by examining an Irish
presidential election. The existence of voting blocs in the electorate is
established and it is determined that age and government satisfaction levels
are important factors in influencing voting in this election.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS178 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Acyclic Games and Iterative Voting
We consider iterative voting models and position them within the general
framework of acyclic games and game forms. More specifically, we classify
convergence results based on the underlying assumptions on the agent scheduler
(the order of players) and the action scheduler (which better-reply is played).
Our main technical result is providing a complete picture of conditions for
acyclicity in several variations of Plurality voting. In particular, we show
that (a) under the traditional lexicographic tie-breaking, the game converges
for any order of players under a weak restriction on voters' actions; and (b)
Plurality with randomized tie-breaking is not guaranteed to converge under
arbitrary agent schedulers, but from any initial state there is \emph{some}
path of better-replies to a Nash equilibrium. We thus show a first separation
between restricted-acyclicity and weak-acyclicity of game forms, thereby
settling an open question from [Kukushkin, IJGT 2011]. In addition, we refute
another conjecture regarding strongly-acyclic voting rules.Comment: some of the results appeared in preliminary versions of this paper:
Convergence to Equilibrium of Plurality Voting, Meir et al., AAAI 2010;
Strong and Weak Acyclicity in Iterative Voting, Meir, COMSOC 201
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