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信息级联与合作崩溃

Information Cascades and the Collapse of Cooperation.

机构信息

Unit 66136 and College of System Engineering, National University of Defense Technology, Changsha, China.

Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary.

出版信息

Sci Rep. 2020 May 14;10(1):8004. doi: 10.1038/s41598-020-64800-z.

Abstract

In various types of structured communities newcomers choose their interaction partners by selecting a role-model and copying their social networks. Participants in these networks may be cooperators who contribute to the prosperity of the community, or cheaters who do not and simply exploit the cooperators. For newcomers it is beneficial to interact with cooperators but detrimental to interact with cheaters. However, cheaters and cooperators usually cannot be identified unambiguously and newcomers' decisions are often based on a combination of private and public information. We use evolutionary game theory and dynamical networks to demonstrate how the specificity and sensitivity of those decisions can dramatically affect the resilience of cooperation in the community. We show that promiscuous decisions (high sensitivity, low specificity) are advantageous for cooperation when the strength of competition is weak; however, if competition is strong then the best decisions for cooperation are risk-adverse (low sensitivity, high specificity). Opportune decisions based on private and public information can still support cooperation but suffer of the presence of information cascades that damage cooperation, especially in the case of strong competition. Our research sheds light on the way the interplay of specificity and sensitivity in individual decision-making affects the resilience of cooperation in dynamical structured communities.

摘要

在各种类型的结构化社区中,新来者通过选择榜样并复制他们的社交网络来选择互动伙伴。这些网络中的参与者可以是为社区繁荣做出贡献的合作者,也可以是不做出贡献、只是利用合作者的骗子。对于新来者来说,与合作者互动是有益的,但与骗子互动则是有害的。然而,骗子和合作者通常不能被明确区分,新来者的决策通常基于私人和公共信息的组合。我们使用进化博弈论和动态网络来展示这些决策的特异性和敏感性如何极大地影响社区中合作的恢复力。我们表明,当竞争强度较弱时,滥交决策(高敏感性、低特异性)有利于合作;然而,如果竞争激烈,那么合作的最佳决策是避险(低敏感性、高特异性)。基于私人和公共信息的适时决策仍然可以支持合作,但会受到信息级联的影响,这些信息级联会损害合作,尤其是在竞争激烈的情况下。我们的研究揭示了个体决策中特异性和敏感性的相互作用如何影响动态结构化社区中合作的恢复力。

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