平行竞赛之间的竞争

IF 1 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS
Xiaotie Deng , Ningyuan Li , Weian Li , Qi Qi
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引用次数: 0

摘要

我们研究了并行举办的多个等级竞赛的模型,其中每个参赛者只选择一个竞赛参加,由每个竞赛设计师决定竞赛的奖品结构。本文首先分析了竞争对手的策略行为,完整地刻画了对称贝叶斯纳什均衡。对于竞赛设计者的策略,当其他设计者的策略已知时,我们证明了计算最佳对策是np困难的,并提出了一个完整的多项式时间近似方案来输出ϵ-approximate最佳对策。当其他设计师的策略未知时,我们对一个设计师的策略进行最坏情况分析。我们给出了任何策略的最坏情况效用的上界,并提出了一种构造策略的方法,该策略的效用在最坏情况下能保证该上界的恒定比率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Competition among parallel contests
We investigate the model of multiple rank-order contests held in parallel, where each contestant only 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 to output the ϵ-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 worst-case 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.
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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
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