适应度作为信息适应度:多层次必要变异的信息理论研究

Martin Hilbert
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引用次数: 0

摘要

这篇文章从一个熟悉的概念开始,即进化可以被认为是处理关于种群结构多样性的不确定性。不确定性的解决通过负熵传递信息,这增加了适应度。这种设置可以一般化。事实证明,信息是种群类型多样性与环境模式及时展开之间的联系。信息在多个层次上的条件作用减少了不确定性,从而增加了适应度。虽然以前的研究已经通过凯利的下注-对冲标准(随机切换)将这种逻辑应用于时间模式,但本文展示了如何将相同的逻辑应用于多层次人口结构。示例包括分类法和地理分布。其结果是将适应度重新定义为进化中的种群与其环境之间的多层次交流过程。多层递归提供了一个单一的设置来研究任何种群层次和环境模式之间的多样性关系。通过下注套期保值的信息理论优化表明,在每种环境状态只有一种特殊类型的情况下,适应度可以优化。这让人想起了必要多样性的概念,并展示了适应度优化是如何通过不断进化的种群和环境模式之间的多层次信息拟合来理解的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fitness as Informational Fit: An Information Theoretic Approach to Multilevel Requisite Variety
The article starts with the familiar notion that evolution can be thought of as handling uncertainty with regard to variety in population structures. The resolution of uncertainty communicates information through negative entropy, which increases fitness. This setup can be generalized. Information turns out to be the link between diversity of types in populations and unfolding environmental patterns in time. Conditioning of information over multiple levels reduces uncertainty, which increases fitness. While previous research has applied this logic to temporal patterns through Kelly’s bet-hedging criteria (stochastic switching), this article shows how the same logic can also be applied to multilevel population structures. Examples include taxonomies and geographic distributions. The result is a reformulation of fitness as a multilevel communication process between the evolving population and its environment. The multilevel recursion provides a single setup to investigate diversity relations between any population hierarchy and environmental patterns. Information theoretic optimization through bet-hedging reveals that fitness can be optimized for the case in which there is one specialized type per environmental state. This is reminiscent of the notion of requisite variety, and shows how fitness optimization can be understood in terms of a multilevel informational fit between the evolving population and environmental patterns.
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