Manipulation of Nanson's and Baldwin's Rules

N. Narodytska, T. Walsh, L. Xia
AAAI 2011
Abstract
Nanson's and Baldwin's voting rules selecta winner by successively eliminatingcandidates with low Borda scores. We showthat these rules have a number of desirablecomputational properties. In particular,with unweighted votes, it isNP-hard to manipulate either rule with one manipulator, whilstwith weighted votes, it isNP-hard to manipulate either rule with a small number ofcandidates and a coalition of manipulators.As only a couple of other voting rulesare known to be NP-hard to manipulatewith a single manipulator, Nanson'sand Baldwin's rules appearto be particularly resistant to manipulation from a theoretical perspective.We also propose a number of approximation methodsfor manipulating these two rules.Experiments demonstrate that both rules areoften difficult to manipulate in practice.These results suggest that elimination stylevoting rules deserve further study.

Remarks: There is a journal version: Jessica Davies, George Katsirelos, Nina Narodytska, Toby Walsh, Lirong Xia: Complexity of and algorithms for the manipulation of Borda, Nanson's and Baldwin's voting rules. Artif. Intell. 217: 20-42 (2014)

Experiments:

Election type Culture Candidates Voters Instances Parameters
Ordinal Impartial Culture {5} {5} 3000 None
Ordinal Urn Model {5} {5} 3000 alpha = 1 (contagion parameter, in the paper refrerred to as a = m!)
Ordinal Impartial Culture {4} {4} 1000 None
Ordinal Impartial Culture {8} {8} 1000 None
Ordinal Impartial Culture {16} {16} 1000 None
Ordinal Impartial Culture {32} {32} 1000 None
Ordinal Impartial Culture {64} {64} 1000 None
Ordinal Impartial Culture {128} {128} 1000 None
Ordinal Urn Model {4} {4} 1000 alpha = 1 (contagion parameter, in the paper refrerred to as a = m!)
Ordinal Urn Model {8} {8} 1000 alpha = 1 (contagion parameter, in the paper refrerred to as a = m!)
Ordinal Urn Model {16} {16} 1000 alpha = 1 (contagion parameter, in the paper refrerred to as a = m!)
Ordinal Urn Model {32} {32} 1000 alpha = 1 (contagion parameter, in the paper refrerred to as a = m!)
Ordinal Urn Model {64} {64} 1000 alpha = 1 (contagion parameter, in the paper refrerred to as a = m!)
Ordinal Urn Model {128} {128} 1000 alpha = 1 (contagion parameter, in the paper refrerred to as a = m!)