自组织和特征形式

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Computation Pub Date : 2023-12-05 DOI:10.3390/computation11120247

Louis H. Kauffman

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引用次数: 0

摘要

本文探讨了由Maturana, Uribe和Varela提出的自创生的形式化模型，并通过特征形式(不动点)的概念和Goedelian编码的复杂性来分析该模型及其含义。本文讨论了自创生与本征形式之间的联系，以及各种不同的观点和例子。本文针对具体实例的各种结论，提出了原创性的哲学思考和概括，旨在为在自然科学的背景下理解生命系统(形式模型)提供一种统一的方式，并从生物构造类似物的角度来看待这些系统的作用和信息的形成。为此，我们关注形式系统和生物系统描述中的不动点、自我参考和自我复制模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Autopoiesis and Eigenform

This paper explores a formal model of autopoiesis as presented by Maturana, Uribe and Varela, and analyzes this model and its implications through the lens of the notions of eigenforms (fixed points) and the intricacies of Goedelian coding. The paper discusses the connection between autopoiesis and eigenforms and a variety of different perspectives and examples. The paper puts forward original philosophical reflections and generalizations about its various conclusions concerning specific examples, with the aim of contributing to a unified way of understanding (formal models of) living systems within the context of natural sciences, and to see the role of such systems and the formation of information from the point of view of analogs of biological construction. To this end, we pay attention to models for fixed points, self-reference and self-replication in formal systems and in the description of biological systems.

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来源期刊

Computation Mathematics-Applied Mathematics

CiteScore

3.50

自引率

4.50%

发文量

201

审稿时长

8 weeks

期刊介绍： Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to: bioinformatics mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions mathematical modeling of pathways and genetic interactions neuroscience computation including neural modeling, brain theory and neural networks computational chemistry, including, but not limited to: new theories and methodology including their applications in molecular dynamics computation of electronic structure density functional theory designing and characterization of materials with computation method computation in engineering, including, but not limited to: new theories, methodology and the application of computational fluid dynamics (CFD) optimisation techniques and/or application of optimisation to multidisciplinary systems system identification and reduced order modelling of engineering systems parallel algorithms and high performance computing in engineering.