Approximately Strategy-Proof Voting Eleanor BirrellRafael Pass Cornell University.
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Transcript of Approximately Strategy-Proof Voting Eleanor BirrellRafael Pass Cornell University.
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Approximately Strategy-Proof Voting
Eleanor Birrell Rafael PassCornell University
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uCharlie (A) = 1 uCharlie (B) = .9uCharlie (C) = .2
The Model
…σAlice = {A,B,C} σBob = {C, A, B} σCharlie = {A,C,B} σZelda = {C,B,A}
A B C
σCharlie (A) > σCharlie (B) σCharlie (B) > σCharlie (C)
Goal: Voters honestly report their preference σ
fGoal: f is strategy-proof Goal: f is strategy-proof
Bad News: Only if f is dictatorial or binary. [Gibb73, Gibb77, Satt75]
ui(j) Є [0,1]
Goal: f is strategy-proof
Bad News: Only if f is trivial. [Gibb73, Gibb77, Satt75]
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Circumventing Gibbard-Satterthwaite
• Hard to manipulate?– BTT89, FKN09, IKM10
• Randomized Approximations?– CS06, Gibb77, Proc10
• Restricted preferences?– Moul80
• Relaxed Problem?
ε - Strategy Proof: By lying, no voter can improve their utility very much
δ - Approximations: f’ returns an outcome that is close to f(σ)
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σAlice σBob σCharlie σZelda
A B
f
C
uCharlie (A) = 1 uCharlie (B) = .9uCharlie (C) = .2
Strategy Proof: By lying (mis-reporting their preference σi), no voter can improve their utility ui .
ε-Strategy Proof: By lying (mis-reporting their preference σi), no voter can improve their utility ui by more than ε.
ɛ-Strategy-Proof Voting
Strategy Proof:
ε-Strategy Proof:
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δ - Approximations
Defining “Close”Defining Approximation
• f’ is a δ-approx. of f if the outcome of f’ is always close to that of f .
• Distance depends on both input and output:
f’(x) = f(y) s.t. Δ(x,y) < δ
σAlice σBob σCharlie σZelda
…σ'Bob σ‘Zelda
A B C0
2
4
6 5
2
4
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Is ε-Strategy Proof Voting Possible?
ε = o (1/n) ε = ω (1/n)
δ = βn No Yes
Theorem 1:
Theorem 2:
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ε-Strategy Proof Voting: A Construction
Deterministic Rule ( f ): Approximation ( f’ ):
d = 5
d = 2
d = 1
d = 3
d = 4
d = 1
d = 2d = 3
d = 4
d = 5
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f
ε-Strategy Proof Voting: A Construction
A
B
C
{A, B, C}
{A, C, B}
{C, A, B}
{C, B, A}0 1 2 3
0
0.2
0.4
0.6
0.8
1
Distance: df( f(σ), j) Prop
ortio
nal P
roba
bilit
y: P
r [ f’
(σ) =
j ]
ξ
A C B1
ε/3
𝛿 Note: Only works
for
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How Good is This?• Every voting rule has a .05-strategy-proof 650-approx.• And a . 01-strategy-proof 3,250-approx.• And a .005-strategy-proof 6,500-approx.• And a .001-strategy-proof 32,500-approx.• And a .0005-strategy-proof 65,000-approx.
Candidate Votes Obama 69,498,215 McCain 59,948,240 Nader 738,720 Baldwin 199,437 McKinney 161,680
Candidate Votes Carpenter 6,582 Fishpaw 5,865 Cole 4,500 Sweeney 1,988 Carlson 1,837
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This is Asymptotically Optimal
h(σ):=
i=1 i=n…
… …j=1 j=kj=1 j=k
Return g(σ)Select player i:
Select rank j:
Prob: kε(k-1) kε(k-k) kε(k-1) kε(k-k) 1 - n∑kε(k-j)j
Punish Deviating
0-strategy proof trivial trivial
0-strategy proof prob. dist. over trivial rules. [Gibb77]
ε-strategy proof prob. dist. over trivial rules (ε = o(1/n)).
ε = o(1/n) no good ε-strategy proof approx of Plurality.
trival no good approx.Reduction: ε-SP to 0-SP
p p
1 - np
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Summaryε = o (1/n) ε = ω (1/n)
δ = βn
Thank you!
• A new technique for circumventing Gibbard-Satterthwaite• Extensions• Small elections? • Uncertainty in inputs?
YesNo