10,470 research outputs found
Weighted Approval Voting
To allow society to treat unequal alternatives distinctly we propose a natural extension of Approval Voting [7] by relaxing the assumption of neutrality. According to this extension, every alternative receives ex-ante a non-negative and finite weight. These weights may differ across alternatives. Given the voting decisions of every individual (individuals are allowed to vote for, or approve of, as many alternatives as they wish to), society elects all alternatives for which the product of total number of votes times exogenous weight is maximal. Our main result is an axiomatic characterization of this voting procedure.microeconomics ;
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
Consistent Probabilistic Social Choice
Two fundamental axioms in social choice theory are consistency with respect
to a variable electorate and consistency with respect to components of similar
alternatives. In the context of traditional non-probabilistic social choice,
these axioms are incompatible with each other. We show that in the context of
probabilistic social choice, these axioms uniquely characterize a function
proposed by Fishburn (Rev. Econ. Stud., 51(4), 683--692, 1984). Fishburn's
function returns so-called maximal lotteries, i.e., lotteries that correspond
to optimal mixed strategies of the underlying plurality game. Maximal lotteries
are guaranteed to exist due to von Neumann's Minimax Theorem, are almost always
unique, and can be efficiently computed using linear programming
Are there any nicely structured preference~profiles~nearby?
We investigate the problem of deciding whether a given preference profile is
close to having a certain nice structure, as for instance single-peaked,
single-caved, single-crossing, value-restricted, best-restricted,
worst-restricted, medium-restricted, or group-separable profiles. We measure
this distance by the number of voters or alternatives that have to be deleted
to make the profile a nicely structured one. Our results classify the problem
variants with respect to their computational complexity, and draw a clear line
between computationally tractable (polynomial-time solvable) and
computationally intractable (NP-hard) questions
Voting rules as statistical estimators
We adopt an `epistemic' interpretation of social decisions: there is an objectively correct choice, each voter receives a `noisy signal' of the correct choice, and the social objective is to aggregate these signals to make the best possible guess about the correct choice. One epistemic method is to fix a probability model and compute the maximum likelihood estimator (MLE), maximum a posteriori estimator (MAP) or expected utility maximizer (EUM), given the data provided by the voters. We first show that an abstract voting rule can be interpreted as MLE or MAP if and only if it is a scoring rule. We then specialize to the case of distance-based voting rules, in particular, the use of the median rule in judgement aggregation. Finally, we show how several common `quasiutilitarian' voting rules can be interpreted as EUM.voting; maximum likelihood estimator; maximum a priori estimator; expected utility maximizer; statistics; epistemic democracy; Condorcet jury theorem; scoring rule
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