文章基本信息

标题：Memory-n strategies of direct reciprocity
本地全文：下载
作者：Christian Hilbe ; Luis A. Martinez-Vaquero ; Krishnendu Chatterjee 等
期刊名称：Proceedings of the National Academy of Sciences
印刷版ISSN：0027-8424
电子版ISSN：1091-6490
出版年度：2017
卷号：114
期号：18
页码：4715-4720
DOI：10.1073/pnas.1621239114
语种：English
出版社：The National Academy of Sciences of the United States of America
摘要：Humans routinely use conditionally cooperative strategies when interacting in repeated social dilemmas. They are more likely to cooperate if others cooperated before, and are ready to retaliate if others defected. To capture the emergence of reciprocity, most previous models consider subjects who can only choose from a restricted set of representative strategies, or who react to the outcome of the very last round only. As players memorize more rounds, the dimension of the strategy space increases exponentially. This increasing computational complexity renders simulations for individuals with higher cognitive abilities infeasible, especially if multiplayer interactions are taken into account. Here, we take an axiomatic approach instead. We propose several properties that a robust cooperative strategy for a repeated multiplayer dilemma should have. These properties naturally lead to a unique class of cooperative strategies, which contains the classical Win–Stay Lose–Shift rule as a special case. A comprehensive numerical analysis for the prisoner’s dilemma and for the public goods game suggests that strategies of this class readily evolve across various memory- n spaces. Our results reveal that successful strategies depend not only on how cooperative others were in the past but also on the respective context of cooperation.
关键词：evolutionary game theory ; reciprocity ; repeated games