进化动力学
人口
进化博弈论
集合(抽象数据类型)
随机博弈
进化稳定策略
复制因子方程
构造(python库)
进化算法
博弈论
计算机科学
数理经济学
人工智能
数学
社会学
人口学
程序设计语言
作者
Corina E. Tarnita,Tibor Antal,Hisashi Ohtsuki,Martin A. Nowak
标识
DOI:10.1073/pnas.0903019106
摘要
Evolutionary dynamics are strongly affected by population structure. The outcome of an evolutionary process in a well-mixed population can be very different from that in a structured population. We introduce a powerful method to study dynamical population structure: evolutionary set theory. The individuals of a population are distributed over sets. Individuals interact with others who are in the same set. Any 2 individuals can have several sets in common. Some sets can be empty, whereas others have many members. Interactions occur in terms of an evolutionary game. The payoff of the game is interpreted as fitness. Both the strategy and the set memberships change under evolutionary updating. Therefore, the population structure itself is a consequence of evolutionary dynamics. We construct a general mathematical approach for studying any evolutionary game in set structured populations. As a particular example, we study the evolution of cooperation and derive precise conditions for cooperators to be selected over defectors.
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