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从固定概率到 d-玩家博弈:演化动力学中的一个反问题。

From Fixation Probabilities to d-player Games: An Inverse Problem in Evolutionary Dynamics.

机构信息

Departamento de Matemática and Centro de Matemática e Apliçoes, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Quinta da Torre, 2829-516, Caparica, Portugal.

Instituto de Matemática e Estatística, Universidade Federal Fluminense, R. Prof. Marcos Waldemar de Freitas Reis, s/n, Niterói, RJ, 24210-201, Brasil.

出版信息

Bull Math Biol. 2019 Nov;81(11):4625-4642. doi: 10.1007/s11538-018-00566-w. Epub 2019 Jan 11.

Abstract

The probability that the frequency of a particular trait will eventually become unity, the so-called fixation probability, is a central issue in the study of population evolution. Its computation, once we are given a stochastic finite population model without mutations and a (possibly frequency dependent) fitness function, is straightforward and it can be done in several ways. Nevertheless, despite the fact that the fixation probability is an important macroscopic property of the population, its precise knowledge does not give any clear information about the interaction patterns among individuals in the population. Here we address the inverse problem: from a given fixation pattern and population size, we want to infer what is the game being played by the population. This is done by first exploiting the framework developed in Chalub and Souza (J Math Biol 75:1735-1774, 2017), which yields a fitness function that realises this fixation pattern in the Wright-Fisher model. This fitness function always exists, but it is not necessarily unique. Subsequently, we show that any such fitness function can be approximated, with arbitrary precision, using d-player game theory, provided d is large enough. The pay-off matrix that emerges naturally from the approximating game will provide useful information about the individual interaction structure that is not itself apparent in the fixation pattern. We present extensive numerical support for our conclusions.

摘要

特定特征的频率最终达到 1 的概率,即所谓的固定概率,是群体进化研究的一个核心问题。一旦我们给定了一个没有突变且(可能依赖频率)适合度函数的随机有限群体模型,其计算就变得简单直接,可以通过几种方法来完成。然而,尽管固定概率是群体的一个重要宏观属性,但它的精确知识并不能提供关于群体中个体之间相互作用模式的任何明确信息。在这里,我们解决了一个相反的问题:从给定的固定模式和群体大小,我们想要推断出群体所进行的博弈。这是通过首先利用 Chalub 和 Souza (J Math Biol 75:1735-1774, 2017)发展的框架来完成的,该框架给出了在 Wright-Fisher 模型中实现该固定模式的适合度函数。这个适合度函数总是存在的,但它不一定是唯一的。随后,我们证明,只要 d 足够大,任何这样的适合度函数都可以使用 d 个玩家博弈论进行近似,具有任意精度。从近似博弈中自然出现的支付矩阵将提供关于个体相互作用结构的有用信息,而这些信息在固定模式中并不明显。我们为我们的结论提供了广泛的数值支持。

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