The continuity of life and its evolution, we have proposed, emerge from an interactive group process termed Survival-of-the-Fitted. This process supplants the Darwinian theory of individual struggle and Survival-of-the-Fittest as the primary mechanism of evolution. Here, we propose that Survival-of-the-Fitted results from a natural process functionally related to computer autoencoding. Autoencoding is a machine-learning technique for extracting a compact representation of the essential features of input data; dimensionality reduction by autoencoding establishes a code that enables a variety of applications based on decoding of the relevant data. We establish the following points: (1) We define a species by its species interaction code, which consists of the fundamental, core interactions of the species with its external and internal environments; core interactions are encoded by multi-scale networks including molecules-cells-organisms. (2) Evolution proceeds by sustainable changes in species interaction codes; these changing codes both reflect and construct the species environment. The survival of species is computed by what we term Natural Autoencoding: arrays of input interactions generate species codes, which survive by decoding into networks of sustained ecosystem interactions. DNA is only one element in Natural Autoencoding. (3) Natural Autoencoding and artificial autoencoding processes manifest defined similarities and differences. Survival-of-the-Fitted by Natural Autoencoding sheds a new light on the mechanism of evolution and explains why a habitable biosphere requires a diversity of fitted group interactions.
翻译:我们建议,生命的连续性及其演化来自一个互动的团体进程,称为“自成一体的生存”的演变过程。这一过程取代了达尔文的个体斗争和自成一体的生存理论,并取代了达尔文的个体斗争和自成一体的生存理论,作为进化的主要机制。在这里,我们提议,从一个与计算机自动编码功能相关的自然过程中获得的自成一体的结果;自动化编码是一种机器学习技术,用于提取输入数据基本特征的缩缩写;通过自动编码减少维度,建立了一个代码,使基于相关数据解码的各种应用得以实现。我们确定以下各点:(1) 我们用其物种互动代码界定物种,其中包括物种与外部和内部环境的基本、核心互动;核心互动由包括分子细胞-生物体在内的多尺度网络编码编码。(2) 通过物种互动代码的可持续变化,这些变化的代码既反映又构建物种环境。 物种的存续存通过我们所谓的“自然自成一体的自成形编码”来计算:一个不断的自然生态系统互动阵列 — 由自成的自成型DNA定义的自动和自成型的DNA模型的网络。