Distant truth: Bias under vote distortion costs

Svetlana Obraztsova, Omer Lev, Evangelos Markakis, Zinovi Rabinovich, Jeffrey S. Rosenschein

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

4 Scopus citations


In recent years, there has been increasing interest within the computational social choice community regarding models where voters are biased towards specific behaviors or have secondary preferences. An important representative example of this approach is the model of truth bias, where voters prefer to be honest about their preferences, unless they are pivotal. This model has been demonstrated to be an effective tool in controlling the set of pure Nash equilibria in a voting game, which otherwise lacks predictive power. However, in the models that have been used thus far, the bias is binary, i.e., the final utility of a voter depends on whether he cast a truthful vote or not, independently of the type of lie. In this paper, we introduce a more robust framework, and eliminate this limitation, by investigating truth-biased voters with variable bias strength. Namely, we assume that even when voters face incentives to lie towards a better out-come, the ballot distortion from their truthful preference incurs a cost, measured by a distance function. We study various such distance-based cost functions and explore their effect on the set of Nash equilibria of the underlying game. Intuitively, one might expect that such distance metrics may induce similar behavior. To our surprise, we show that the presented metrics exhibit quite different equilibrium behavior.

Original languageEnglish
Title of host publication16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
EditorsSanmay Das, Edmund Durfee, Kate Larson, Michael Winikoff
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Number of pages8
ISBN (Electronic)9781510855076
StatePublished - 1 Jan 2017
Externally publishedYes
Event16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017 - Sao Paulo, Brazil
Duration: 8 May 201712 May 2017

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914


Conference16th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017
CitySao Paulo


  • Dynamics
  • TV uth-bias
  • Voting

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering


Dive into the research topics of 'Distant truth: Bias under vote distortion costs'. Together they form a unique fingerprint.

Cite this