Solving the prisoner’s dilemma trap in Hamilton’s model of temporarily formed random groups

IF 1.9 4区 数学 Q2 BIOLOGY
José F. Fontanari , Mauro Santos
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引用次数: 0

Abstract

Explaining the evolution of cooperation in the strong altruism scenario, where a cooperator does not benefit from her contribution to the public goods, is a challenging problem that requires positive assortment among cooperators (i.e., cooperators must tend to associate with other cooperators) or punishment of defectors. The need for these drastic measures stems from the analysis of a group selection model of temporarily formed random groups introduced by Hamilton nearly fifty years ago to describe the fate of altruistic behavior in a population. Challenging conventional wisdom, we show analytically here that strong altruism evolves in Hamilton’s original model in the case of biparental sexual reproduction. Moreover, when the cost of cooperation is small and the amplified contribution shared by group members is large, cooperation is the only stable strategy in equilibrium. Thus, our results provide a solution to the ‘problem of origination’ of strong altruism, i.e. how cooperation can take off from an initial low frequency of cooperators. We discuss a possible reassessment of cooperation in cases of viral co-infection, as cooperation may even be favored in situations where the prisoner’s dilemma applies.

在汉密尔顿的临时随机群体模型中破解囚徒困境陷阱
在强利他主义情况下,合作者不会从其对公共产品的贡献中获益,要解释这种情况下的合作演化是一个具有挑战性的问题,需要在合作者之间进行正向分类(即合作者必须倾向于与其他合作者交往)或惩罚叛逃者。采取这些严厉措施的必要性源于汉密尔顿(Hamilton)近五十年前提出的群体选择模型,该模型由临时形成的随机群体组成,用于描述群体中利他行为的命运。与传统观点不同,我们在这里通过分析表明,在汉密尔顿最初的模型中,在双亲有性繁殖的情况下,会出现强烈的利他主义。此外,当合作成本较小且群体成员共享的放大贡献较大时,合作是均衡状态下唯一稳定的策略。因此,我们的研究结果为强利他主义的 "起源问题 "提供了一个解决方案,即合作如何从最初的低合作频率开始。我们讨论了在病毒共同感染的情况下重新评估合作的可能性,因为在适用囚徒困境的情况下,合作甚至可能更有利。
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来源期刊
CiteScore
4.20
自引率
5.00%
发文量
218
审稿时长
51 days
期刊介绍: The Journal of Theoretical Biology is the leading forum for theoretical perspectives that give insight into biological processes. It covers a very wide range of topics and is of interest to biologists in many areas of research, including: • Brain and Neuroscience • Cancer Growth and Treatment • Cell Biology • Developmental Biology • Ecology • Evolution • Immunology, • Infectious and non-infectious Diseases, • Mathematical, Computational, Biophysical and Statistical Modeling • Microbiology, Molecular Biology, and Biochemistry • Networks and Complex Systems • Physiology • Pharmacodynamics • Animal Behavior and Game Theory Acceptable papers are those that bear significant importance on the biology per se being presented, and not on the mathematical analysis. Papers that include some data or experimental material bearing on theory will be considered, including those that contain comparative study, statistical data analysis, mathematical proof, computer simulations, experiments, field observations, or even philosophical arguments, which are all methods to support or reject theoretical ideas. However, there should be a concerted effort to make papers intelligible to biologists in the chosen field.
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