Speaker: Ariel Procaccia Joint work with: Michael Zuckerman, Jeff Rosenschein Hebrew University of Jerusalem
Background: Intro to voting. Hardness of manipulation. Coalitional manipulation. A greedy algorithm. New results: characterization of alg’s window of error. Implications w.r.t. approximation.
Agents have to reach a consensus regarding a preferred alternative in a shared environment. Examples: Joint plans. Beliefs. Recommendations. Voting theory gives a well studied framework for preference aggregation. 3
Set of voters V={1,...,n}. Set of Candidates C={a,b,c...}; |C|=m. Voters (strictly) rank the candidates. Preference profile: a vector of rankings. Voting rule: maps preference profiles to candidates. Plurality. Borda. Voter 1Voter 2Voter 3 a b c a c b b c a
Often it is in the voters’ interest to reveal false preferences. May lead to the election of a socially bad candidate. 5 pab
Theorem (Gibbard-Satterthwaite): any nondictatorial voting rule is manipulable. Circumvent Gibbard-Satterthwaite by: Mechanism design. Single-peaked preferences. [Bartholdi et al. SC&W 89]: Computational hardness to the rescue! [Bartholdi and Orlin SC&W 91]: STV is NP- hard to manipulate. A lot of recent work.
A coalition of manipulators cooperates in order to make p C win the election. Votes are weighted. Formulation as decision problem (CCWM): Instance: a set of weighted votes which have been cast, the weights of the manipulators, p C. Question: Can p win the election? Conitzer et al. [JACM 07]: NP-hard for a variety of voting rules, even when m is constant.
Worst-case hardness is not a strong guarantee. Is there a voting rule which is hard to manipulate on a large fraction of the instances? Apparently not? Conitzer and Sandholm [AAAI 06]: Instance can be manipulated efficiently if: Weakly monotone. A second, problematic property. Voter 1Voter 2 Voter 3 a b b c a d c b d a d c
Worst-case hardness is not a strong guarantee. Is there a voting rule which is hard to manipulate on a large fraction of the instances? Apparently not?
Procaccia and Rosenschein [JAIR 07]: Junta distributions are hard. Susceptibility to manipulation if can manipulate with high prob. w.r.t. a Junta distribution. Scoring rules are susceptible; very loose bound on the error window of a greedy algorithm. Only scoring rules and other limitations.
Reminder: in Borda, each voter awards m-k points to candidate ranked k. Reminder: CCWM Instance: a set of weighted votes which have been cast, the weights of the manipulators, p C. Question: Can p win the election? Greedy algorithm for coalitional manipulation [Procaccia and Rosenschein, JAIR 07]: each manipulator ranks p first, and the other candidates by inverse score.
pab
pab
Theorem: Let W be the list of weights for the manipulators. 1. If there is no manipulation, the greedy alg will return false. 2. If there is a manipulation, then for the same instance with weights W+{w 1,...,w k }, where w i max W, the alg will return true. In particular, can add one manipulator with weight max W.
pab
Algorithm fails Manipulation exists All instances
Conjecture: unweighted coalitional manipulation (CCUM) is NP-complete in Borda. CCUO: given (unweighted) votes of truthful voters, how many manipulators are needed to make p win? Theorem (saw earlier): Let W be the list of weights. In Borda manipulators need additional max W. Corollary: Approximation of CCUO in Borda to additive 1.
Similar results for three other voting rules: Maximin, Plurality with runoff, Veto.