ML Anthology

Margin of Victory in Tournaments: Structural and Experimental Results

Markus Brill, Ulrike Schmidt-Kraepelin, Warut Suksompong
AAAI 2021 pp. 5228-5235
doi:10.1609/AAAI.V35I6.16660 /aaai/2021/brill2021aaai-margin/

Abstract

Tournament solutions are standard tools for identifying winners based on pairwise comparisons between competing alternatives. The recently studied notion of margin of victory (MoV) offers a general method for refining the winner set of any given tournament solution, thereby increasing the discriminative power of the solution. In this paper, we reveal a number of structural insights on the MoV by investigating fundamental properties such as monotonicity and consistency with respect to the covering relation. Furthermore, we provide experimental evidence on the extent to which the MoV notion refines winner sets in tournaments generated according to various stochastic models.

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Text

Brill et al. "Margin of Victory in Tournaments: Structural and Experimental Results." AAAI Conference on Artificial Intelligence, 2021. doi:10.1609/AAAI.V35I6.16660

Markdown

[Brill et al. "Margin of Victory in Tournaments: Structural and Experimental Results." AAAI Conference on Artificial Intelligence, 2021.](https://mlanthology.org/aaai/2021/brill2021aaai-margin/) doi:10.1609/AAAI.V35I6.16660

BibTeX

@inproceedings{brill2021aaai-margin,
  title     = {{Margin of Victory in Tournaments: Structural and Experimental Results}},
  author    = {Brill, Markus and Schmidt-Kraepelin, Ulrike and Suksompong, Warut},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2021},
  pages     = {5228-5235},
  doi       = {10.1609/AAAI.V35I6.16660},
  url       = {https://mlanthology.org/aaai/2021/brill2021aaai-margin/}
}