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Anonymity-Proof Voting Rules

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Internet and Network Economics (WINE 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5385))

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Abstract

A (randomized, anonymous) voting rule maps any multiset of total orders (aka. votes) over a fixed set of alternatives to a probability distribution over these alternatives. A voting rule f is false-name-proof if no voter ever benefits from casting more than one vote. It is anonymity-proof if it satisfies voluntary participation and it is false-name-proof. We show that the class of anonymity-proof neutral voting rules consists exactly of the rules of the following form. With some probability k f  ∈ [0,1], the rule chooses an alternative uniformly at random. With probability 1 − k f , the rule first draws a pair of alternatives uniformly at random. If every vote prefers the same alternative between the two (and there is at least one vote), then the rule chooses that alternative. Otherwise, the rule flips a fair coin to decide between the two alternatives. We also show how the characterization changes if group strategy-proofness is added as a requirement.

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Author information

Authors and Affiliations

  1. Departments of Computer Science and Economics, Duke University, Durham, NC, USA

    Vincent Conitzer

Authors
  1. Vincent Conitzer
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Editor information

Editors and Affiliations

  1. Computer Science Division, University of California at Berkeley, Berkeley, CA, USA

    Christos Papadimitriou

  2. Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong

    Shuzhong Zhang

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© 2008 Springer-Verlag Berlin Heidelberg

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Conitzer, V. (2008). Anonymity-Proof Voting Rules. In: Papadimitriou, C., Zhang, S. (eds) Internet and Network Economics. WINE 2008. Lecture Notes in Computer Science, vol 5385. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92185-1_36

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  • DOI: https://doi.org/10.1007/978-3-540-92185-1_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92184-4

  • Online ISBN: 978-3-540-92185-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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