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Gibbard–Satterthwaite theorem

The Gibbard–Satterthwaite theorem is a result in social choice theory proving that no deterministic social choice function can be strategy-proof and non-dictatorial when there are at least three alternatives and at least two voters.^[1]^[2] Named after Allan Gibbard, who published the proof in 1973, and Mark Allen Satterthwaite, whose independent demonstration appeared in 1975, the theorem establishes that voters can always benefit from misrepresenting their true preferences in some preference profile unless the outcome is controlled by a single dictatorial voter.^[1]^[2] A voting procedure is strategy-proof if sincere preference revelation is a dominant strategy for every voter, meaning no individual can achieve a preferred outcome by submitting a false ballot regardless of others' reports.^[1] The theorem's proof relies on revealing a pivotal voter whose unilateral preference shift alters the collective decision, enabling manipulation by adjusting reported rankings to exploit that pivotality.^[3] This impossibility underscores fundamental limits in designing incentive-compatible mechanisms for aggregating ordinal preferences, influencing subsequent work in mechanism design and computational social choice by showing that randomization or additional assumptions (like restricted domains) are often necessary to approximate strategy-proofness.^[3]^[4]

Statement of the Theorem

Informal Description

The Gibbard–Satterthwaite theorem establishes that no non-dictatorial voting procedure can be strategy-proof when there are at least three alternatives and voters report complete ordinal preferences. A strategy-proof procedure ensures that, for any voter's true preferences and any fixed reports from others, submitting a false preference ranking cannot yield a more preferred outcome for that voter. The theorem proves that any such procedure must either grant dictatorial power to a single voter—whose top-ranked alternative always wins—or fail to be "onto," meaning some alternative can never win regardless of reported preferences.^[4]^[5] This impossibility arises because distributing decisional influence across multiple voters creates opportunities for manipulation: a pivotal voter, whose report can swing the outcome between undesired results, has incentive to misreport to avoid worse alternatives and secure a better one. For example, in systems like plurality voting, a voter might strategically rank a less-preferred candidate higher to block a disliked frontrunner. The result holds for deterministic social choice functions mapping preference profiles to winners, revealing why real-world elections often exhibit tactical voting despite incentives for sincerity.^[4]^[6]

Formal Statement

The Gibbard–Satterthwaite theorem applies to deterministic social choice functions in environments with a finite set of voters N where |N| \geq 2, a finite set of alternatives A where |A| \geq 3, and strict individual preferences represented as linear orders over A. Let \mathcal{L}(A) denote the set of all linear orders on A. A preference profile is R = (R_i)_{i \in N} \in \mathcal{L}(A)^N. A social choice function is f: \mathcal{L}(A)^N \to A. The function f is strategy-proof if, for every profile R, every voter i \in N, and every alternative preference R_i' \in \mathcal{L}(A), the outcome under truthful reporting is at least as preferred by i (according to R_i) as the outcome under misrepresentation: f(R) \succeq_{R_i} f(R_{-i}, R_i'), where \succeq_{R_i} denotes the weak order induced by R_i and R_{-i} denotes the profile with i's preferences removed. Equivalently, no voter can obtain a strictly preferred outcome by unilaterally misreporting their preferences.^[7]^[8] The function f is onto (or surjective) if every alternative in A is selected as the outcome for at least one preference profile: \{f(R) \mid R \in \mathcal{L}(A)^N\} = A. A function f is dictatorial if there exists a voter i \in N such that, for every profile R, f(R) is the unique most-preferred alternative of i under R_i: f(R) = \max_{R_i} A.^[7]^[8] The theorem states: Any strategy-proof and onto social choice function f is dictatorial.^[7]^[8] This holds under the universal domain assumption that all possible strict preference profiles are admissible.^[9]

Corollary

The Gibbard–Satterthwaite theorem implies that no non-dictatorial social choice function selecting a single alternative from a set of at least three can be both strategy-proof and onto, meaning every such function permits strategic manipulation by at least one voter under some preference profile.^[10] This follows directly from the theorem's conditions, as non-dictatorship and onto-ness preclude strategy-proofness, rendering common voting procedures like plurality or Borda count vulnerable to incentive incompatibility unless restricted to two alternatives or dictatorial selection.^[11] The theorem is equivalent in logical strength to Arrow's impossibility theorem and can be derived as its corollary. Specifically, a strategy-proof and onto social choice function is Pareto efficient and monotonic; by the Muller-Satterthwaite theorem, any such function satisfying Pareto efficiency and monotonicity must be dictatorial, yielding the Gibbard–Satterthwaite result.^[10]^[11] Conversely, Arrow's theorem follows from Gibbard–Satterthwaite by extending the social choice function to a full social welfare ordering via transitive closure, preserving the required properties.^[11] This equivalence underscores that strategic manipulability in winner selection mirrors the impossibility of non-dictatorial aggregation of ordinal preferences into consistent rankings under independence of irrelevant alternatives and Pareto efficiency.^[10]

Proof

Sketch of Proof

Strategy-proofness of a social choice function implies monotonicity: if changing a single voter's reported preference to rank an alternative X higher (while keeping it preferred to the previous winner) results in a different outcome, then X must become the winner.^[6]^[5] To prove the theorem, assume a non-dictatorial function f that is strategy-proof, unanimous, and defined over at least three alternatives A, B, C. Fix alternative B. By unanimity, B wins if all voters rank it first. By onto-ness (or range at least three alternatives), there exists a profile where B wins. Consider profiles where voters 1 through k rank B first (and agree on the rest), while the rest rank B last: there is a minimal pivotal r such that B loses for k < r but wins for k = r. In profiles where voters r through n rank B last (and the first r-1 rank it first), strategy-proofness and monotonicity imply voter r's top-ranked alternative (say K) must win when others rank B last but agree on rankings above B.^[5]^[6] Repeating for other alternatives shows the pivotal voter is the same individual across all, who dictates the outcome: their top choice always wins by monotonicity and the pivotal construction, contradicting the non-dictatorial assumption. Thus, no such function exists.^[12]^[6]

Exceptions and Counterexamples

Dictatorial Voting Rules

A dictatorial voting rule, also known as a dictatorship mechanism, is a social choice function where the outcome is determined solely by the strict preference ordering of a single designated voter, the dictator, such that the selected alternative is always that voter's most preferred option among the feasible set, regardless of the reported preferences of all other voters.^[13]^[14] Such rules satisfy the onto condition of the Gibbard–Satterthwaite theorem, as every alternative can be selected if it ranks first in the dictator's ordering.^[15] Dictatorial rules are strategy-proof because the dictator has no incentive to misrepresent their preferences: truthful reporting ensures their true top-ranked alternative is chosen, while any deviation could only select a less preferred option or fail to alter the outcome favorably.^[16] For non-dictator voters, unilateral deviation cannot influence the outcome, as it depends exclusively on the dictator's report, rendering manipulation unprofitable.^[17] Thus, dictatorships constitute the sole class of non-manipulable voting rules under the theorem's assumptions of at least three alternatives, non-constancy, and surjectivity, though they fail to aggregate preferences democratically by rendering all but one voter irrelevant.^[15]^[16]

Cardinal and Non-Rank-Order Systems

The Gibbard–Satterthwaite theorem presupposes that voters submit complete strict ordinal rankings of alternatives, with the social choice function defined over the universal domain of such rankings. Cardinal voting systems, by contrast, elicit numerical utilities or scores from voters, enabling the expression of preference intensities beyond mere ordering. This richer input domain means the theorem's proof, which relies on manipulations within the space of linear orders, does not directly extend to cardinal mechanisms. For instance, range voting requires voters to assign scores (e.g., from 0 to 10) to each alternative, aggregating via mean or sum to select the highest-scoring option.^[18] Nevertheless, achieving dominant-strategy incentive compatibility in cardinal systems for non-dictatorial selection of one alternative from three or more remains impossible under standard conditions. Any continuous strategy-proof cardinal voting mechanism effectively discards cardinal information, depending solely on the ordinal rankings induced by the reported utilities, and thus inherits the theorem's impossibility for non-dictatorial rules satisfying citizen sovereignty (Pareto efficiency).^[19] Discontinuities might in principle allow use of intensities, but such mechanisms risk non-existence or violation of basic rationality axioms like anonymity or neutrality.^[20] Non-rank-order systems, such as approval voting (where voters approve or reject subsets of alternatives) or cumulative voting (assigning points across candidates without full ranking), similarly evade the theorem's ordinal domain assumption. In approval voting, the winner is typically the alternative with the most approvals; strategic behavior involves adjusting approval sets to influence outcomes, but the lack of required full rankings prevents direct application of the theorem's universal domain traversal in proofs. These systems often exhibit manipulation opportunities, though potentially less severe or frequent than in pure ordinal methods, as voters cannot fully simulate arbitrary rankings. Empirical analyses indicate approval voting can be less manipulable in expectation under incomplete information, but no non-dictatorial variant achieves full strategy-proofness.^[18]^[21]

Other Loopholes and Special Cases

The Gibbard–Satterthwaite theorem applies only when there are at least three alternatives; with exactly two alternatives, simple majority rule is strategy-proof, as no voter can benefit from misreporting their strict preference, since the outcome is determined solely by the number of supporters for each option without opportunities for strategic inversion.^[11]^[5] A primary loophole arises from restricting the domain of admissible preferences, which circumvents the theorem's unrestricted-domain assumption and permits non-dictatorial strategy-proof rules. For instance, on domains of single-peaked preferences—where voters' ideal points lie on a linear structure and preferences decrease monotonically away from the peak—the median voter rule selects the alternative at the median of voters' peaks and is strategy-proof, as any deviation by a voter cannot shift the median in their favor without worsening their outcome.^[22] More generally, every surjective strategy-proof social choice function on single-peaked domains is a generalized median voter scheme, incorporating fixed ranges or anonymous medians that aggregate peaks while preserving incentive compatibility.^[22]^[23] Similar domain restrictions enable strategy-proofness in other structured settings. Under single-crossing preferences—where voters are ordered such that preference intensities cross at most once along the ordering—strategy-proof rules exist that are non-dictatorial, such as generalized medians adapted to the crossing structure, avoiding manipulation by ensuring deviations do not profitably alter the crossing point's influence.^[24] These cases highlight how embedding realistic preference constraints, empirically observed in spatial or ideological voting, resolves the impossibility by limiting the preference profiles to those without cycles or strategic leverage points inherent in unrestricted domains.^[25] Further special cases include partial or incomplete preferences, where relaxing completeness allows non-dictatorial strategy-proof functions by constraining the feasible reports to subsets where manipulation is infeasible, though such relaxations significantly narrow applicability compared to full ordinal rankings.^[26]

History

Origins and Independent Proofs

The Gibbard–Satterthwaite theorem originated with Allan Gibbard's proof in his 1973 paper "Manipulation of Voting Schemes: A General Result," published in Econometrica. Gibbard established that no voting scheme with at least three alternatives can be non-dictatorial and immune to individual strategic manipulation, meaning some voter can benefit by misrepresenting preferences under certain profiles. His approach generalized beyond voting to game forms without utilities, proving that strategy-proof forms are either unilateral (one player's choice determines the outcome, akin to dictatorship) or duple (outcomes restricted to two options decisive for the group).^[1]^[7] Independently, Mark Allen Satterthwaite provided a proof in his 1975 paper "Strategy-Proofness and Arrow's Conditions: Existence and Correspondence Theorems for Voting Procedures and Social Welfare Functions," appearing in the Journal of Economic Theory. Satterthwaite showed that for voting procedures with three or more alternatives, strategy-proofness implies dictatorship if the procedure is onto (every alternative can win) and satisfies basic unanimity. His result connected strategy-proofness in voting to Arrow's independence of irrelevant alternatives and non-dictatorship conditions, deriving from his 1973 doctoral dissertation at the University of Michigan.^[2]^[27] The independent discoveries, with Gibbard's preceding Satterthwaite's publication by two years, underscored the theorem's robustness across game-theoretic and social choice frameworks, leading to its eponymous naming despite the slight temporal offset. Both proofs addressed a long-standing conjecture on voting manipulability, building on earlier work without resolving it directly.^[28]

Subsequent Developments

In 1977, Allan Gibbard extended the Gibbard–Satterthwaite theorem to probabilistic social choice functions that mix voting with randomization, proving that no such non-dictatorial mechanism is strategy-proof when voters possess von Neumann–Morgenstern preferences over lotteries, as strategic misrepresentation can still alter expected utilities in the manipulator's favor.^[29] This generalization highlighted the theorem's robustness beyond deterministic rules, influencing analyses of hybrid mechanisms where chance supplements ordinal voting.^[30] The theorem spurred characterizations of strategy-proof social choice on restricted preference domains during the late 1970s and 1980s, where non-dictatorial rules become feasible, such as median-based selection under single-peaked preferences. Salvador Barberà's contributions, including foundational work on pivotal mechanisms and group strategy-proofness, demonstrated that strategy-proof functions on structured domains often rely on voters whose preferences decisively influence outcomes without full dictatorship.^[31] These developments shifted focus from universal impossibilities to domain-specific possibilities, enabling applications like location theory and public good provision. Refinements to proofs of the theorem continued into the 1990s and beyond, with Svensson (1999) offering a concise revelation-based argument that avoids complex manipulations.^[32] Later, quantitative extensions in the 2010s, such as those by Mossel and Procaccia (2010), used geometric methods to bound the probability of successful manipulation, providing measurable approximations to strategy-proofness for practical voting rules.^[33]

Connections to Arrow's Theorem

The Gibbard–Satterthwaite theorem and Arrow's impossibility theorem both establish impossibility results in social choice theory, demonstrating that non-dictatorial aggregation of ordinal preferences fails under minimal fairness conditions when there are at least three alternatives. Arrow's theorem applies to social welfare functions that produce a complete social ordering satisfying Pareto efficiency (unanimity) and independence of irrelevant alternatives (IIA), concluding that such functions must be dictatorial.^[34] In contrast, the Gibbard–Satterthwaite theorem concerns social choice functions that select a single winner and are strategy-proof (non-manipulable), onto, and Pareto efficient, also yielding dictatorship.^[11] The theorems share core assumptions like Pareto efficiency and non-dictatorship, with strategy-proofness in the former linking to monotonicity, which parallels IIA in restricting how preference changes affect outcomes.^[10] A key connection arises from the Muller–Satterthwaite theorem, which states that a social choice function is both Pareto efficient and monotonic only if dictatorial, serving as an intermediate result that bridges to Gibbard–Satterthwaite by showing strategy-proofness implies these properties.^[10] Gibbard–Satterthwaite can be derived as a corollary of Arrow's theorem by constructing a social welfare function from the social choice function: iteratively apply the choice function to preference profiles, rank the selected alternative highest, and extend to a full linear order that satisfies Pareto efficiency and IIA, forcing dictatorship and thus implying the choice function is dictatorial.^[11] This reduction highlights how selecting a maximal element under a social ordering inherits Arrow's constraints.^[34] Reny (2001) further unifies the theorems via a single proof structure employing pivotal voter arguments, proving a monotonicity-based version akin to Muller–Satterthwaite (yielding Gibbard–Satterthwaite) and adapting it to IIA for Arrow's result, emphasizing their logical equivalence under shared efficiency and neutrality conditions.^[10] These links underscore that strategy-proof winner selection embeds the full-ranking impossibilities of Arrow, with dictatorship emerging from the inability to aggregate without privileging one voter.^[34]

Gibbard's Theorem on Strategy-Proofness

In 1977, Allan Gibbard characterized the class of strategy-proof randomized social decision schemes, which aggregate individual preferences into a probability distribution over outcomes. A social decision scheme is strategy-proof if, for any von Neumann-Morgenstern utility function consistent with an agent's true preferences, truthful reporting is a dominant strategy, meaning no agent can increase their expected utility by misreporting preferences regardless of others' reports.^[29] Gibbard's theorem states that such a scheme must be a probability mixture of unilateral and duple schemes. Unilateral schemes select an outcome based solely on a single agent's reported preference ordering, effectively implementing a random dictatorship by randomizing over agents or fixed outcomes per agent. Duple schemes restrict outcomes to exactly two alternatives and select between them in a strategy-proof manner, often equivalent to always choosing one fixed alternative or conditioning the choice on whether a designated agent's preference aligns with a specific ordering between the pair.^[29] This characterization extends beyond deterministic settings by incorporating randomization, yet reveals that strategy-proofness severely limits non-dictatorial aggregation even with lotteries. For instance, in environments with three or more alternatives, non-trivial mixtures cannot achieve Pareto efficiency or range over all possible outcomes without vulnerability to manipulation. The proof relies on revealing local non-manipulability conditions: if a scheme is manipulable at some profile, it implies a contradiction with global strategy-proofness via utility perturbations and continuity arguments over preference domains. Gibbard assumes universal domains of strict preferences and connectedness of the outcome space, ensuring the result applies broadly to ordinal social choice under expected utility maximization.^[29] Gibbard's result implies that the only strategy-proof randomized rules satisfying citizen sovereignty (every alternative winning under some preference profile) and anonymity (equal treatment of agents) are random dictatorships, mixtures of unilaterals where each agent has positive probability of dictatorial power. Duplets, while strategy-proof, fail sovereignty as they ignore most alternatives. This theorem generalizes the deterministic Gibbard-Satterthwaite impossibility by showing randomization does not circumvent manipulability without sacrificing desirable properties like non-dictatorship. Subsequent work, such as Gibbard's own 1973 deterministic characterization of strategy-proof set-valued functions as dictatorial, aligns as a special case where mixtures degenerate to single unilaterals.^[29]^[35]

Implications and Extensions

The Gibbard–Satterthwaite theorem constitutes a cornerstone impossibility result in social choice theory, proving that no non-dictatorial social choice function can be strategy-proof when there are at least three alternatives and at least two voters.^[11] This demonstrates the intrinsic manipulability of deterministic ordinal voting rules that satisfy universality (every alternative can win under some profile) and Pareto efficiency, as at least one voter can benefit from misrepresenting preferences in some scenarios.^[36] The theorem's proof, via reduction to dictatorial outcomes or contradiction with non-manipulability, underscores that truthful voting cannot be enforced without assigning unilateral control to a single individual.^[12] Its theoretical weight lies in exposing the limits of aggregating heterogeneous preferences into coherent collective choices, paralleling but distinct from Arrow's theorem by prioritizing incentive compatibility over interpersonal comparability or independence of irrelevant alternatives.^[11] Unlike binary-choice settings where majority rule achieves strategy-proofness, the theorem reveals that expanding alternatives introduces unavoidable strategic incentives, rendering sincere revelation unstable in multi-option environments.^[36] This has reframed social choice as inherently game-theoretic, prompting analyses of voter behavior under incomplete information or bounded rationality to mitigate manipulation risks.^[12] The theorem's influence permeates mechanism design, where it necessitates trade-offs such as probabilistic outcomes or restricted domains to approximate non-manipulability, as pure strategy-proofness remains unattainable without dictatorship.^[11] It informs critiques of real-world electoral systems, explaining empirical observations of tactical voting, and drives extensions to set-valued or stochastic functions that evade the impossibility under relaxed single-valuedness.^[37] Overall, by quantifying the causal link between preference diversity and strategic instability, the result enforces realism in modeling institutional incentives, emphasizing that decentralized decision-making inherently invites exploitation unless constrained by additional structure.^[11]

Applications in Mechanism Design

The Gibbard–Satterthwaite theorem underscores fundamental limitations in designing dominant-strategy incentive-compatible (DSIC) mechanisms for social choice problems with unrestricted ordinal preferences and at least three alternatives, implying that only dictatorial outcomes can satisfy strategy-proofness and onto properties without side payments.^[38] In mechanism design, this impossibility drives the field toward circumventions such as incorporating transferable utility, where quasilinear preferences allow Vickrey-Clarke-Groves (VCG) mechanisms to achieve DSIC allocation and efficient outcomes by compensating agents via transfers that internalize externalities.^[39] For instance, in multi-unit auctions or public goods provision, VCG implements the efficient allocation truthfully, as deviations cannot increase an agent's utility net of transfers.^[40] Domain restrictions provide another escape, enabling strategy-proof mechanisms on structured preference spaces; under single-peaked preferences, the median voter rule selects the median-reported peak as the outcome, which is DSIC and Pareto efficient.^[41] Similarly, in matching markets or assignment problems, serial dictatorship—where agents are ordered and sequentially pick top choices—avoids manipulation while respecting ordinal rankings, applicable in school choice or housing allocations with coarse priorities.^[42] These approaches exploit the theorem's inapplicability outside unrestricted domains, prioritizing empirical feasibility over generality. Randomization further mitigates the theorem's constraints, as probabilistic mechanisms like random dictatorship—randomly selecting an agent's preference as decisive—are ex-ante strategy-proof, though not DSIC, and extend to Gibbard's random social choice functions for fairer implementations.^[43] In computational mechanism design, approximations relax exact truthfulness; for example, mechanisms with bounded approximation ratios to optimal welfare maintain approximate incentive compatibility, vital for large-scale platforms like ad auctions where full efficiency is infeasible.^[44] Recent generalizations quantify manipulability, informing hybrid designs that balance incentives with performance in Bayesian settings.^[45] Overall, the theorem compels designers to trade off universality for practicality, shaping robust implementations in economics and computer science.^[11]

Quantitative and Approximate Versions

Quantitative versions of the Gibbard–Satterthwaite theorem quantify the extent of manipulability by showing that, for non-dictatorial social choice functions, a positive fraction of preference profiles admit successful strategic manipulation by at least one voter. In a 2010 result by Isaksson, Kindler, and Mossel, for neutral social choice functions over three or more alternatives, a uniformly random voter profile has a constant fraction (at least 1/16) of "manipulation points," where a single voter's truthful report leads to a non-optimal outcome for them, and deviating to another report improves it.^[46] This bound holds under the assumption of neutral rules, where permutations of alternatives yield permuted outcomes, and extends the existential impossibility to an average-case analysis over the space of all possible preference profiles.^[47] Friedgut, Kalai, Keller, and Nisan extended this in 2011 to demonstrate that, for three alternatives, a randomly selected manipulation by a single randomly chosen voter succeeds with probability at least \Omega(1/\log n) over uniform random profiles with n voters, where success means the manipulator's preferred alternative wins instead of a less preferred one.^[48] This non-negligible probability underscores that manipulability is not rare but occurs frequently in typical settings, even for computationally simple rules like plurality voting.^[49] Xia and Conitzer's 2011 theorem generalizes these results to non-neutral social choice functions for any number k \geq 3 of alternatives, proving that the fraction of profiles where at least one voter can manipulate to gain their top-ranked alternative is bounded below by \Omega(1/\poly(k \log n)), removing the neutrality assumption while preserving the quantitative flavor.^[50] These bounds rely on probabilistic methods and Fourier analysis over the Boolean cube of preference orderings, providing explicit measures of vulnerability rather than mere existence.^[51] Approximate versions explore relaxations where mechanisms are \epsilon-strategy-proof, meaning no voter gains more than \epsilon utility by deviating, but deterministic voting rules remain dictatorial even under this weakening, as a direct corollary of the original theorem.^[52] In randomized settings, Procaccia and Rosenschein (2006) showed that no non-trivial randomized rule is fully strategy-proof, but approximate strategy-proofness allows for rules like random dictatorships, where expected utility loss from manipulation is bounded.^[52] Further, Dütting, Gkatzelis, and Roughgarden (2010) examined whether approximation ratios in social welfare can circumvent Gibbard–Satterthwaite-like impossibilities, finding that for voting, even constant-factor approximations often fail to yield strategy-proof mechanisms without dictatorship, though hybrid or coarse approximations (e.g., via partitions of alternatives) permit partial circumvention in mechanism design contexts beyond pure voting.^[53] These approximations quantify trade-offs, such as requiring \epsilon = \Omega(1) for non-trivial welfare maximization under strategy-proofness constraints.^[54]

Recent Advances and Generalizations

Reffgen (2011) extended the Gibbard–Satterthwaite theorem to settings where voters report partial preferences modeled as acyclic binary relations rather than complete strict orders. Under assumptions of onto social choice functions and a weak Pareto efficiency condition, non-dictatorial rules remain manipulable, as a voter can profitably deviate by refining or altering their reported relation to influence the outcome in their favor.^[55] The same work further generalizes to multi-valued social choice rules, which select sets of alternatives rather than singletons, defining strategy-proofness such that no voter benefits from misreporting to change the selected set in a way that worsens their evaluation of it. Such rules must be dictatorial in a generalized sense, where one voter's preferences unilaterally determine the entire set for all profiles consistent with universal rankings of the alternatives.^[55] Reffgen also quantified the degree of manipulability, showing that the minimal number of profiles requiring manipulation for non-dictatorial rules grows with the number of voters and alternatives, but remains unavoidable.^[55] Sekiguchi, Kamijo, and Hanaki (2023) provided a novel topological proof of the theorem, constructing a space of preference profiles endowed with the product topology and a space of outcomes, then using continuity of the social choice function and fixed-point theorems to derive the dictatorial characterization without relying on traditional inductive or constructive arguments. This approach highlights structural properties of the preference domain, potentially aiding extensions to continuous or infinite settings. Independently, Bade and Gonczarowski (2016) connected the theorem to obvious strategy-proofness, a relaxation where strategic deviations are not visibly beneficial even under limited foresight; while full strategy-proofness remains impossible beyond dictatorships, obviously strategy-proof rules like serial dictatorships emerge as practical approximations on unrestricted domains, evading Gibbard–Satterthwaite pathologies for cognitively bounded agents.^[44]

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Mar 8, 1999 · The objective of this paper is to present short and very simple proofs of the classical Gibbard s Satterthwaite theorem (Gibbard (1973), ...<|separator|>
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[PDF] a Quantitative Proof of the Gibbard Satterthwaite Theorem
The Gibbard-Satterthwaite theorem has contributed signifi- cantly to the realization that it is unlikely to expect truthfulness. Page 2. in the context of ...
[34]
[PDF] Gibbard Satterthwaite Theorem and Arrow Impossibility Theorem
In this section, we discuss the Gibbard–Satterthwaite impossibility theorem (G–S theorem, for short), which shows that the DSIC property will force an. SCF to ...
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Manipulation of Voting Schemes: A General Result - Semantic Scholar
Jul 1, 1973 · It has been conjectured that no system of voting can preclude strategic voting-the securing by a voter of an outcome he prefers through ...
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None
### Summary of Gibbard-Satterthwaite Theorem and Its Importance
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A topological proof of the Gibbard–Satterthwaite theorem
It delivers a striking message: the only voting rules which are not vulnerable to strategic manipulation are dictatorships. This fact not only has important ...
[38]
[PDF] impossibility of strategy-proof mechanisms - Princeton University
The Gibbard-Satterthwaite Theorem gives a negative answer to this question for the case in which the space of admissible preferences is unrestricted. It states ...Missing: explanation | Show results with:explanation<|separator|>
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[PDF] Mechanism Design - University of Waterloo
Theorem. Groves mechanisms are strategy-proof and efficient. We have gotten around Gibbard-Satterthwaite. Page 34. Mechanism. Design. Kate Larson. Introduction.Missing: applications | Show results with:applications
[40]
The Theory of Mechanism Design: An Overview - jstor
aspect of the theory of mechanism design. Suppose that there are N voters ... ed by the Gibbard-Satterthwaite Theorem. [Gibbard 1973; Satterthwaite 1975] ...
[41]
[PDF] Theory of Mechanism Design - Indian Statistical Institute, Delhi
Nov 13, 2014 · domain which is restricted, and the Gibbard-Satterthwaite theorem does not apply. We now formally define the single-peaked preferences. Let ...
[42]
[PDF] Gibbard-Satterthwaite Success Stories and Obvious Strategyproofness
Mar 18, 2017 · The Gibbard-Satterthwaite Impossibility Theorem ... The concern with incentives sets mechanism design apart from algorithm and protocol de-.
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The Gibbard random dictatorship theorem: a generalization and a ...
Mar 1, 2011 · Sen A (2001) Another direct proof of the Gibbard–Satterthwaite ... Salvador Barberà is one of the pioneers in probabilistic mechanism design ...<|separator|>
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Gibbard-Satterthwaite Success Stories and Obvious Strategyproofness
Oct 16, 2016 · The Gibbard-Satterthwaite Impossibility Theorem holds that dictatorship is the only Pareto optimal and strategyproof social choice function on ...
[45]
[PDF] a Quantitative Proof of the Gibbard Satterthwaite Theorem - arXiv
Apr 12, 2010 · The Gibbard-Satterthwaite theorem presented a difficulty in designing social choice functions, namely that of strategic voting. A line of ...
[46]
https://ieeexplore.ieee.org/document/5671191
[47]
[PDF] a Quantitative Proof of the Gibbard Satterthwaite Theorem
Abstract—We prove a quantitative version of the Gibbard-. Satterthwaite theorem. We show that a uniformly chosen voter profile for a neutral social choice ...
[48]
A Quantitative Version of the Gibbard-Satterthwaite Theorem ... - arXiv
May 25, 2011 · Abstract:The Gibbard-Satterthwaite theorem states that every non-dictatorial election rule among at least three alternatives can be ...
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A Quantitative Version of the Gibbard–Satterthwaite Theorem for ...
The Gibbard–Satterthwaite theorem states that every nondictatorial election rule among at least three alternatives can be strategically manipulated.
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A quantitative gibbard-satterthwaite theorem without neutrality
Recently, quantitative versions of the Gibbard-Satterthwaite theorem were proven for k=3 alternatives by Friedgut, Kalai, Keller and Nisan and for neutral ...
[51]
[PDF] A Quantitative Gibbard-Satterthwaite Theorem without Neutrality
A quantitative Gibbard-Satterthwaite theorem for one voter. A major part of the work in proving Theo- rem 1.2 is devoted to understanding functions of a single ...Missing: explanation | Show results with:explanation
[52]
[PDF] Approximately Strategy-Proof Voting - Cornell: Computer Science
The first, proven independently by Gibbard [1973] and Satterthwaite [1975], demonstrates that only a trivial col- lection of voting rules are strategy-proof.
[53]
Can Approximation Circumvent Gibbard-Satterthwaite?
Jul 4, 2010 · The Gibbard-Satterthwaite Theorem asserts that any reasonable voting rule cannot be strategyproof. A large body of research in AI deals with ...
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[PDF] Can Approximation Circumvent Gibbard-Satterthwaite? - CS.HUJI
Abstract. The Gibbard-Satterthwaite Theorem asserts that any reason- able voting rule cannot be strategyproof. A large body of re-.
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Generalizing the Gibbard–Satterthwaite theorem: partial preferences ...
Aug 18, 2010 · The Gibbard–Satterthwaite (GS) theorem is generalized in three ways: First, it is proved that the theorem is still valid when individual ...