79 research outputs found

    A quantitative Gibbard-Satterthwaite theorem without neutrality

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    Recently, quantitative versions of the Gibbard-Satterthwaite theorem were proven for k=3k=3 alternatives by Friedgut, Kalai, Keller and Nisan and for neutral functions on k≥4k \geq 4 alternatives by Isaksson, Kindler and Mossel. We prove a quantitative version of the Gibbard-Satterthwaite theorem for general social choice functions for any number k≥3k \geq 3 of alternatives. In particular we show that for a social choice function ff on k≥3k \geq 3 alternatives and nn voters, which is ϵ\epsilon-far from the family of nonmanipulable functions, a uniformly chosen voter profile is manipulable with probability at least inverse polynomial in nn, kk, and ϵ−1\epsilon^{-1}. Removing the neutrality assumption of previous theorems is important for multiple reasons. For one, it is known that there is a conflict between anonymity and neutrality, and since most common voting rules are anonymous, they cannot always be neutral. Second, virtual elections are used in many applications in artificial intelligence, where there are often restrictions on the outcome of the election, and so neutrality is not a natural assumption in these situations. Ours is a unified proof which in particular covers all previous cases established before. The proof crucially uses reverse hypercontractivity in addition to several ideas from the two previous proofs. Much of the work is devoted to understanding functions of a single voter, and in particular we also prove a quantitative Gibbard-Satterthwaite theorem for one voter.Comment: 46 pages; v2 has minor structural changes and adds open problem

    The Geometry of Manipulation — A Quantitative Proof of the Gibbard Satterthwaite Theorem

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    We prove a quantitative version of the Gibbard-Satterthwaite theorem. We show that a uniformly chosen voter profile for a neutral social choice function f of q ≥ 4 alternatives and n voters will be manipulable with probability at least 10−4∈2 n −3 q −30, where ∈ is the minimal statistical distance between f and the family of dictator functions. Our results extend those of [11], which were obtained for the case of 3 alternatives, and imply that the approach of masking manipulations behind computational hardness (as considered in [4,6,9,15,7]) cannot hide manipulations completely. Our proof is geometric. More specifically it extends the method of canonical paths to show that the measure of the profiles that lie on the interface of 3 or more outcomes is large. To the best of our knowledge our result is the first isoperimetric result to establish interface of more than two bodies

    The Pareto Frontier for Random Mechanisms

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    We study the trade-offs between strategyproofness and other desiderata, such as efficiency or fairness, that often arise in the design of random ordinal mechanisms. We use approximate strategyproofness to define manipulability, a measure to quantify the incentive properties of non-strategyproof mechanisms, and we introduce the deficit, a measure to quantify the performance of mechanisms with respect to another desideratum. When this desideratum is incompatible with strategyproofness, mechanisms that trade off manipulability and deficit optimally form the Pareto frontier. Our main contribution is a structural characterization of this Pareto frontier, and we present algorithms that exploit this structure to compute it. To illustrate its shape, we apply our results for two different desiderata, namely Plurality and Veto scoring, in settings with 3 alternatives and up to 18 agents.Comment: Working Pape

    A Topological Proof of The Gibbard-Satterthwaite Theorem

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    We give a new proof of the Gibbard-Satterthwaite Theorem. We construct two topological spaces: one for the space of preference profiles and another for the space of outcomes. We show that social choice functions induce continuous mappings between the two spaces. By studying the properties of this mapping, we prove the theorem

    A Generalized Probabilistic Gibbard-Satterthwaite Theorem

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    Friedgut, Kalai, and Nisan have proved that social choice functions can be successfully manipulated by random preference reordering with non- negligible probability. However, their results require two restrictions: the social choice function must be neutral, and the election must have at most 3 alternatives. In this thesis we focus on removing the latter restriction and generalizing the results to elections with any number of candidates. We also provide a survey of related work analyzing and comparing results from a number of authors

    Voting with Coarse Beliefs

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    The classic Gibbard-Satterthwaite theorem says that every strategy-proof voting rule with at least three possible candidates must be dictatorial. Similar impossibility results hold even if we consider a weaker notion of strategy-proofness where voters believe that the other voters' preferences are i.i.d.~(independent and identically distributed). In this paper, we take a bounded-rationality approach to this problem and consider a setting where voters have "coarse" beliefs (a notion that has gained popularity in the behavioral economics literature). In particular, we construct good voting rules that satisfy a notion of strategy-proofness with respect to coarse i.i.d.~beliefs, thus circumventing the above impossibility results

    A Smooth Transition from Powerlessness to Absolute Power

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    We study the phase transition of the coalitional manipulation problem for generalized scoring rules. Previously it has been shown that, under some conditions on the distribution of votes, if the number of manipulators is o(n)o(\sqrt{n}), where nn is the number of voters, then the probability that a random profile is manipulable by the coalition goes to zero as the number of voters goes to infinity, whereas if the number of manipulators is ω(n)\omega(\sqrt{n}), then the probability that a random profile is manipulable goes to one. Here we consider the critical window, where a coalition has size cnc\sqrt{n}, and we show that as cc goes from zero to infinity, the limiting probability that a random profile is manipulable goes from zero to one in a smooth fashion, i.e., there is a smooth phase transition between the two regimes. This result analytically validates recent empirical results, and suggests that deciding the coalitional manipulation problem may be of limited computational hardness in practice.Comment: 22 pages; v2 contains minor changes and corrections; v3 contains minor changes after comments of reviewer
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