Can We Predict the Election Outcome from Sampled Votes?


  • Evi Micha University of Toronto
  • Nisarg Shah University of Toronto



In the standard model of voting, it is assumed that a voting rule observes the ranked preferences of each individual over a set of alternatives and makes a collective decision. In practice, however, not every individual votes. Is it possible to make a good collective decision for a group given the preferences of only a few of its members? We propose a framework in which we are given the ranked preferences of k out of n individuals sampled from a distribution, and the goal is to predict what a given voting rule would output if applied on the underlying preferences of all n individuals. We focus on the family of positional scoring rules, derive a strong negative result when the underlying preferences can be arbitrary, and discover interesting phenomena when they are generated from a known distribution.




How to Cite

Micha, E., & Shah, N. (2020). Can We Predict the Election Outcome from Sampled Votes?. Proceedings of the AAAI Conference on Artificial Intelligence, 34(02), 2176-2183.



AAAI Technical Track: Game Theory and Economic Paradigms