在二进制竞赛中提供昂贵的信息

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Noam Simon, Priel Levy, David Sarne
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引用次数: 0

摘要

在多代理环境中,竞赛通常被用作一种激发努力和参与的机制。自然,与其他各种机制一样,在竞赛之前和整个竞赛过程中向代理提供的信息会从根本上影响竞赛结果。在本文中,我们研究的是当竞赛组织者最初并不掌握信息,而获取信息又可能代价高昂时的信息提供问题。作为模型的基础竞赛机制,我们使用二元竞赛,参赛者的策略由他们是否参加竞赛的决定决定。在这种情况下,竞赛组织者往往可以主动获取并向参赛者提供与他们在竞赛中的预期表现相关的信息。我们对模型进行了全面的均衡分析,结果表明,即使这些信息是无成本的,比赛组织者也不一定会倾向于获取并向所有参赛者提供这些信息,更不用说这些信息是有成本的了。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Costly information providing in binary contests

Contests are commonly used as a mechanism for eliciting effort and participation in multi-agent settings. Naturally, and much like with various other mechanisms, the information provided to the agents prior to and throughout the contest fundamentally influences its outcomes. In this paper we study the problem of information providing whenever the contest organizer does not initially hold the information and obtaining it is potentially costly. As the underlying contest mechanism for our model we use the binary contest, where contestants’ strategy is captured by their decision whether or not to participate in the contest in the first place. Here, it is often the case that the contest organizer can proactively obtain and provide contestants information related to their expected performance in the contest. We provide a comprehensive equilibrium analysis of the model, showing that even when such information is costless, it is not necessarily the case that the contest organizer will prefer to obtain and provide it to all agents, let alone when the information is costly.

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来源期刊
Annals of Mathematics and Artificial Intelligence
Annals of Mathematics and Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
3.00
自引率
8.30%
发文量
37
审稿时长
>12 weeks
期刊介绍: Annals of Mathematics and Artificial Intelligence presents a range of topics of concern to scholars applying quantitative, combinatorial, logical, algebraic and algorithmic methods to diverse areas of Artificial Intelligence, from decision support, automated deduction, and reasoning, to knowledge-based systems, machine learning, computer vision, robotics and planning. The journal features collections of papers appearing either in volumes (400 pages) or in separate issues (100-300 pages), which focus on one topic and have one or more guest editors. Annals of Mathematics and Artificial Intelligence hopes to influence the spawning of new areas of applied mathematics and strengthen the scientific underpinnings of Artificial Intelligence.
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