Toward Fair and Strategyproof Tournament Rules for Tournaments with Partially Transferable Utilities
<|reference_start|>Toward Fair and Strategyproof Tournament Rules for Tournaments with Partially Transferable Utilities: A tournament on $n$ agents is a complete oriented graph with the agents as vertices and edges that describe the win-loss outcomes of the $\binom{n}{2}$ matches played between each pair of agents. The winner of a tournament is determined by a tournament rule that maps tournaments to probability distributions over the agents. We want these rules to be fair (choose a high-quality agent) and robust to strategic manipulation. Prior work has shown that under minimally fair rules, manipulations between two agents can be prevented when utility is nontransferable but not when utility is completely transferable. We introduce a partially transferable utility model that interpolates between these two extremes using a selfishness parameter $\lambda$. Our model is that an agent may be willing to lose on purpose, sacrificing some of her own chance of winning, but only if the colluding pair's joint gain is more than $\lambda$ times the individual's sacrifice.   We show that no fair tournament rule can prevent manipulations when $\lambda < 1$. We computationally solve for fair and manipulation-resistant tournament rules for $\lambda = 1$ for up to 6 agents. We conjecture and leave as a major open problem that such a tournament rule exists for all $n$. We analyze the trade-offs between ``relative'' and ``absolute'' approximate strategyproofness for previously studied rules and derive as a corollary that all of these rules require $\lambda \geq \Omega(n)$ to be robust to manipulation. We show that for stronger notions of fairness, non-manipulable tournament rules are closely related to tournament rules that witness decreasing gains from manipulation as the number of agents increases.<|reference_end|>
@article{pennock2024toward,
    title={Toward Fair and Strategyproof Tournament Rules for Tournaments with
  Partially Transferable Utilities},
    author={David Pennock, Ariel Schvartzman, Eric Xue},
    journal={arXiv preprint arXiv:2408.10346},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.10346},
    primaryClass={cs.GT}
}