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Maximal lotteries

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Maximal lotteries are a probabilistic voting rule that use ranked ballots and returns a lottery over candidates that a majority of voters will prefer, on average, to any other.[1] In other words, in a series of repeated head-to-head matchups, voters will (on average) prefer the results of a maximal lottery to the results produced by any other voting rule.

Maximal lotteries satisfy a wide range of desirable properties: they elect the Condorcet winner with probability 1 if it exists[1] and never elect candidates outside the Smith set.[1] Moreover, they satisfy reinforcement,[2] participation,[3] and independence of clones.[2] The probabilistic voting rule that returns all maximal lotteries is the only rule satisfying reinforcement, Condorcet-consistency, and independence of clones.[2] The social welfare function that top-ranks maximal lotteries has been uniquely characterized using Arrow's independence of irrelevant alternatives and Pareto efficiency.[4]

Maximal lotteries do not satisfy the standard notion of strategyproofness, as Allan Gibbard has shown that only random dictatorships can satisfy strategyproofness and ex post efficiency.[5] Maximal lotteries are also nonmonotonic in probabilities, i.e. it is possible that the probability of an alternative decreases when a voter ranks this alternative up.[1] However, they satisfy relative monotonicity, i.e., the probability of x {\displaystyle x} {\displaystyle x} relative to that of y {\displaystyle y} {\displaystyle y} does not decrease when x {\displaystyle x} {\displaystyle x} is improved over y {\displaystyle y} {\displaystyle y}.[6]

The support of maximal lotteries, which is known as the essential set or the bipartisan set, has been studied in detail.[7] [8] [9] [10]

History

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Maximal lotteries were first proposed by the French mathematician and social scientist Germain Kreweras in 1965[11] and popularized by Peter Fishburn.[1] Since then, they have been rediscovered multiple times by economists,[8] mathematicians,[1] [12] political scientists, philosophers,[13] and computer scientists.[14]

Several natural dynamics that converge to maximal lotteries have been observed in biology, physics, chemistry, and machine learning.[15] [16] [17]

Collective preferences over lotteries

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The input to this voting system consists of the agents' ordinal preferences over outcomes (not lotteries over alternatives), but a relation on the set of lotteries can be constructed in the following way: if p {\displaystyle p} {\displaystyle p} and q {\displaystyle q} {\displaystyle q} are lotteries over alternatives, p q {\displaystyle p\succ q} {\displaystyle p\succ q} if the expected value of the margin of victory of an outcome selected with distribution p {\displaystyle p} {\displaystyle p} in a head-to-head vote against an outcome selected with distribution q {\displaystyle q} {\displaystyle q} is positive. In other words, p q {\displaystyle p\succ q} {\displaystyle p\succ q} if it is more likely that a randomly selected voter will prefer the alternatives sampled from p {\displaystyle p} {\displaystyle p} to the alternative sampled from q {\displaystyle q} {\displaystyle q} than vice versa.[4] While this relation is not necessarily transitive, it does always admit at least one maximal element.

It is possible that several such maximal lotteries exist, as a result of ties. However, the maximal lottery is unique whenever the number of voters is odd.[18] By the same argument, the bipartisan set is uniquely defined by taking the support of the unique maximal lottery that solves a tournament game.[8]

Strategic interpretation

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Maximal lotteries are equivalent to mixed maximin strategies (or Nash equilibria) of the symmetric zero-sum game given by the pairwise majority margins. As such, they have a natural interpretation in terms of electoral competition between two political parties[19] and can be computed in polynomial time via linear programming.

Example

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Suppose there are five voters who have the following preferences over three alternatives:

  • 2 voters: a b c {\displaystyle a\succ b\succ c} {\displaystyle a\succ b\succ c}
  • 2 voters: b c a {\displaystyle b\succ c\succ a} {\displaystyle b\succ c\succ a}
  • 1 voter: c a b {\displaystyle c\succ a\succ b} {\displaystyle c\succ a\succ b}

The pairwise preferences of the voters can be represented in the following skew-symmetric matrix, where the entry for row x {\displaystyle x} {\displaystyle x} and column y {\displaystyle y} {\displaystyle y} denotes the number of voters who prefer x {\displaystyle x} {\displaystyle x} to y {\displaystyle y} {\displaystyle y} minus the number of voters who prefer y {\displaystyle y} {\displaystyle y} to x {\displaystyle x} {\displaystyle x}.

a b c a b c ( 0 1 1 1 0 3 1 3 0 ) {\displaystyle {\begin{matrix}{\begin{matrix}&&a\quad &b\quad &c\quad \\\end{matrix}}\\{\begin{matrix}a\\b\\c\\\end{matrix}}{\begin{pmatrix}0&1&-1\\-1&0&3\1円&-3&0\\\end{pmatrix}}\end{matrix}}} {\displaystyle {\begin{matrix}{\begin{matrix}&&a\quad &b\quad &c\quad \\\end{matrix}}\\{\begin{matrix}a\\b\\c\\\end{matrix}}{\begin{pmatrix}0&1&-1\\-1&0&3\1円&-3&0\\\end{pmatrix}}\end{matrix}}}

This matrix can be interpreted as a zero-sum game and admits a unique Nash equilibrium (or minimax strategy) p {\displaystyle p} {\displaystyle p} where p ( a ) = 3 / 5 {\displaystyle p(a)=3/5} {\displaystyle p(a)=3/5}, p ( b ) = 1 / 5 {\displaystyle p(b)=1/5} {\displaystyle p(b)=1/5}, p ( c ) = 1 / 5 {\displaystyle p(c)=1/5} {\displaystyle p(c)=1/5}. By definition, this is also the unique maximal lottery of the preference profile above. The example was carefully chosen not to have a Condorcet winner. Many preference profiles admit a Condorcet winner, in which case the unique maximal lottery will assign probability 1 to the Condorcet winner. If the last voter in the example above swaps alternatives a {\displaystyle a} {\displaystyle a} and c {\displaystyle c} {\displaystyle c} in his preference relation, a {\displaystyle a} {\displaystyle a} becomes the Condorcet winner and will be selected with probability 1.

References

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  1. ^ a b c d e f Fishburn, P. C. (1984). "Probabilistic Social Choice Based on Simple Voting Comparisons". The Review of Economic Studies. 51 (4): 683–692. doi:10.2307/2297786. ISSN 0034-6527.
  2. ^ a b c F. Brandl, F. Brandt, and H. G. Seedig. Consistent probabilistic social choice. Econometrica. 84(5), pages 1839-1880, 2016.
  3. ^ F. Brandl, F. Brandt, and J. Hofbauer. Welfare Maximization Entices Participation. Games and Economic Behavior. 14, pages 308-314, 2019.
  4. ^ a b F. Brandl and F. Brandt. Arrovian Aggregation of Convex Preferences. Econometrica. 88(2), pages 799-844, 2020.
  5. ^ Gibbard, Allan (1977). "Manipulation of Schemes that Mix Voting with Chance" . Econometrica. 45 (3): 665–681. doi:10.2307/1911681. hdl:10419/220534 . ISSN 0012-9682. JSTOR 1911681.
  6. ^ Brandl, Florian; Brandt, Felix; Stricker, Christian (2022年01月01日). "An analytical and experimental comparison of maximal lottery schemes". Social Choice and Welfare. 58 (1): 5–38. doi:10.1007/s00355-021-01326-x. hdl:10419/286729 . ISSN 1432-217X.
  7. ^ B. Dutta and J.-F. Laslier. Comparison functions and choice correspondences. Social Choice and Welfare, 16: 513–532, 1999.
  8. ^ a b c G. Laffond, J.-F. Laslier, and M. Le Breton. The bipartisan set of a tournament game. Games and Economic Behavior, 5(1):182–201, 1993.
  9. ^ Laslier, J.-F. Tournament solutions and majority voting Springer-Verlag, 1997.
  10. ^ Brandt, Felix; Brill, Markus; Seedig, Hans Georg; Suksompong, Warut (2018年03月01日). "On the structure of stable tournament solutions". Economic Theory. 65 (2): 483–507. doi:10.1007/s00199-016-1024-x. ISSN 0938-2259.
  11. ^ G. Kreweras. Aggregation of preference orderings. In Mathematics and Social Sciences I: Proceedings of the seminars of Menthon-Saint-Bernard, France (1–27 July 1960) and of Gösing, Austria (3–27 July 1962), pages 73–79, 1965.
  12. ^ Fisher, David C.; Ryan, Jennifer (1995). "Tournament games and positive tournaments". Journal of Graph Theory. 19 (2): 217–236. doi:10.1002/jgt.3190190208. ISSN 1097-0118.
  13. ^ Felsenthal, Dan S.; Machover, Moshé (1992). "After two centuries, should condorcet's voting procedure be implemented?". Behavioral Science. 37 (4): 250–274. doi:10.1002/bs.3830370403. ISSN 1099-1743.
  14. ^ R. L. Rivest and E. Shen. An optimal single-winner preferential voting system based on game theory. In Proceedings of 3rd International Workshop on Computational Social Choice, pages 399–410, 2010.
  15. ^ Laslier, Benoît; Laslier, Jean-François (2017年10月01日). "Reinforcement learning from comparisons: Three alternatives are enough, two are not". The Annals of Applied Probability. 27 (5): 2907–2925. doi:10.1214/16-AAP1271. ISSN 1050-5164.
  16. ^ Grilli, Jacopo; Barabás, György; Michalska-Smith, Matthew J.; Allesina, Stefano (2017年08月01日). "Higher-order interactions stabilize dynamics in competitive network models". Nature. 548 (7666): 210–213. doi:10.1038/nature23273. ISSN 1476-4687.
  17. ^ F. Brandl and F. Brandt. A Natural Adaptive Process for Collective Decision-Making. Theoretical Economics 19(2): 667–703, 2024.
  18. ^ Laffond, Gilbert; Laslier, Jean-Francois; Le Breton, Michel (1997年02月01日). "A Theorem on Symmetric Two-Player Zero-Sum Games". Journal of Economic Theory. 72 (2): 426–431. doi:10.1006/jeth.1996.2215. ISSN 0022-0531.
  19. ^ Laslier, J.-F. Interpretation of electoral mixed strategies. Social Choice and Welfare 17: pages 283–292, 2000.
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  • voting.ml (website for computing maximal lotteries)

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