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arXiv 1801.02550q-bio.PE
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从固定概率到d-玩家博弈:演化动力学中的一个逆问题

From fixation probabilities to d-player games: an inverse problem in evolutionary dynamics

Fabio A. C. C. Chalub, Max O. Souza

摘要:

特定性状的频率最终成为统一的概率,即所谓的固定概率,是种群进化研究中的一个中心问题。它的计算,一旦我们给出一个没有突变的随机有限种群模型和一个(可能依赖于频率的)适应度函数,是简单的,它可以通过几种方式完成。然而,尽管注视概率是种群的一个重要的宏观性质,但它的精确知识并不能给出种群中个体之间相互作用模式的任何明确信息。在这里,我们解决了相反的问题:从一个给定的固定模式和人口规模,我们想推断出人口正在玩什么游戏。这是通过首先利用FACC Chalub和MO Souza,J.Math.Biol.75:1735,2017中开发的框架来完成的,其产生在赖特-费舍尔模型中实现该注视模式的适应度函数。这个适应度函数总是存在的,但它不一定是唯一的。随后,我们表明,任何这样的适应度函数可以近似,任意精度,使用$d$球员博弈论,提供$d$是足够大的。从近似博弈中自然出现的支付矩阵将提供关于个体互动结构的有用信息,这些信息本身在注视模式中并不明显。我们提出了广泛的数值支持我们的结论。

英文摘要:

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 FACC Chalub and MO Souza, J. Math. Biol. 75: 1735, 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.

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