We investigate the model of multiple contests held in parallel, where each contestant selects one contest to join and each contest designer decides the prize structure to compete for the participation of contestants. We first analyze the strategic behaviors of contestants and completely characterize the symmetric Bayesian Nash equilibrium. As for the strategies of contest designers, when other designers' strategies are known, we show that computing the best response is NP-hard and propose a fully polynomial time approximation scheme (FPTAS) to output the $\epsilon$-approximate best response. When other designers' strategies are unknown, we provide a worst case analysis on one designer's strategy. We give an upper bound on the utility of any strategy and propose a method to construct a strategy whose utility can guarantee a constant ratio of this upper bound in the worst case.
翻译:我们同时调查多个竞赛的模式,每个参赛者选择一个参赛者,每个参赛者选择一个参赛者选择一个参赛者,而每个参赛者决定奖项结构以竞争参赛者参赛者参赛。我们首先分析参赛者的战略行为,并完整地描述对称巴伊西亚纳什平衡。关于参赛设计者的战略,当其他设计者的战略为人所知时,我们显示计算最佳反应的最佳办法是NP硬的,并提议一个完全的多元时间近似计划(FPTAS ) 来输出$-epslon$-posbound 最佳反应。当其他设计者的战略未知时,我们给出了对一个设计者战略最差的个案分析。我们给任何战略的效用设定了上限,并提出了一种方法来构建战略,其效用可以保证最坏情况下这一上限的利用率不变。