Empirical analysis of plurality election equilibria

David R.M. Thompson, Omer Lev, Kevin Leyton-Brown, Jeffrey Rosenschein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

29 Scopus citations

Abstract

Voting is widely used to aggregate the different preferences of agents, even though these agents are often able to manipulate the outcome through strategic voting. Most research on manipulation of voting methods studies (1) limited solution concepts, (2) limited preferences, or (3) scenarios with a few manipulators that have a common goal. In contrast, we study voting in plurality elections through the lens of Nash equilibrium, which allows for the possibility that any number of agents, with arbitrary different goals, could all be manipulators. This is possible thanks to recent advances in (Bayes-)Nash equilibrium computation for large games. Although plurality has numerous pure-strategy Nash equilibria, we demonstrate how a simple equilibrium refinement - assuming that agents only deviate from truthfulness when it will change the outcome - dramatically reduces this set. We also use symmetric Bayes-Nash equilibria to investigate the case where voters are uncertain of each others' preferences. This refinement does not completely eliminate the problem of multiple equilibria. However, it does show that even when agents manipulate, plurality still tends to lead to good outcomes (e.g., Condorcet winners, candidates that would win if voters were truthful, outcomes with high social welfare).

Original languageEnglish GB
Title of host publication12th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2013), May 2013, St. Paul, Minnesota
Pages391-398
Number of pages8
StatePublished - 1 Jan 2013
Externally publishedYes
Event12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013 - Saint Paul, MN, United States
Duration: 6 May 201310 May 2013

Conference

Conference12th International Conference on Autonomous Agents and Multiagent Systems 2013, AAMAS 2013
Country/TerritoryUnited States
CitySaint Paul, MN
Period6/05/1310/05/13

Keywords

  • Game theory
  • Social choice theory
  • Voting protocols

ASJC Scopus subject areas

  • Artificial Intelligence

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