Preferences Single-Peaked on a Tree: Sampling and Tree Recognition

Jakub Sliwinski, Edith Elkind

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence

Main track. Pages 580-586.

https://doi.org/10.24963/ijcai.2019/82

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Abstract

In voting theory, impossibility results and computational hardness results are often circumvented by recognising that voters' preferences are not arbitrary, but lie within a restricted domain. Uncovering the structure of the underlying domain often provides useful insights about the nature of the alternative space, and may be helpful in identifying a collective choice. Preferences single-peaked on a tree are an example of a relatively broad domain that nonetheless exhibits several desirable properties. We consider the setting where voters' preferences are independently sampled from rankings that are single-peaked on a given tree, and study the problem of reliably identifying the tree that generated the observed votes. We test our algorithm empirically; to this end, we develop an algorithm to uniformly sample preferences that are single-peaked on a given tree.

Keywords

  • Agent-based and Multi-agent Systems: Computational Social Choice
  • Agent-based and Multi-agent Systems: Voting
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