Refining Tournament Solutions via Margin of Victory

Authors

  • Markus Brill Technische Universit„t Berlin
  • Ulrike Schmidt-Kraepelin Technische Universit„t Berlin
  • Warut Suksompong University of Oxford

DOI:

https://doi.org/10.1609/aaai.v34i02.5554

Abstract

Tournament solutions are frequently used to select winners from a set of alternatives based on pairwise comparisons between alternatives. Prior work has shown that several common tournament solutions tend to select large winner sets and therefore have low discriminative power. In this paper, we propose a general framework for refining tournament solutions. In order to distinguish between winning alternatives, and also between non-winning ones, we introduce the notion of margin of victory (MoV) for tournament solutions. MoV is a robustness measure for individual alternatives: For winners, the MoV captures the distance from dropping out of the winner set, and for non-winners, the distance from entering the set. In each case, distance is measured in terms of which pairwise comparisons would have to be reversed in order to achieve the desired outcome. For common tournament solutions, including the top cycle, the uncovered set, and the Banks set, we determine the complexity of computing the MoV and provide worst-case bounds on the MoV for both winners and non-winners. Our results can also be viewed from the perspective of bribery and manipulation.

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Published

2020-04-03

How to Cite

Brill, M., Schmidt-Kraepelin, U., & Suksompong, W. (2020). Refining Tournament Solutions via Margin of Victory. Proceedings of the AAAI Conference on Artificial Intelligence, 34(02), 1862-1869. https://doi.org/10.1609/aaai.v34i02.5554

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Section

AAAI Technical Track: Game Theory and Economic Paradigms