从许多耦合极性振荡器中产生的动态网络:人工生命的范例。

IF 1.3 4区 生物学 Q3 BIOLOGY Theory in Biosciences Pub Date : 2023-09-01 DOI:10.1007/s12064-023-00401-4
Alessandro Scirè, Valerio Annovazzi-Lodi
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引用次数: 1

摘要

这项工作涉及一个多体确定性模型,该模型显示了类似生命的特性,如涌现、复杂性、自组织、自我调节、兴奋性和自发划分。该模型描述了在二维空间中运动的局部耦合极性相振子系综的动力学,在某些条件下表现出涌现的上层结构。这些上层建筑是自组织的动态网络,由许多单元的同步过程产生,其长度尺度远远大于相互作用范围。由于多孔传输壁的形成,这种网络在没有先验约束的情况下划分了二维空间,并代表了一种高度复杂和新颖的非线性行为。数值分析作为控制参数的函数进行,显示出不同的状态:静态模式形成、动态可激网络形成、间歇性和混沌。绘制统计分析来确定各种行为出现的控制参数范围。该模型和结果有望为人工生命领域做出贡献。
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The emergence of dynamic networks from many coupled polar oscillators: a paradigm for artificial life.

This work concerns a many-body deterministic model that displays life-like properties such as emergence, complexity, self-organization, self-regulation, excitability and spontaneous compartmentalization. The model portraits the dynamics of an ensemble of locally coupled polar phase oscillators, moving in a two-dimensional space, that under certain conditions exhibit emergent superstructures. Those superstructures are self-organized dynamic networks, resulting from a synchronization process of many units, over length scales much greater than the interaction range. Such networks compartmentalize the two-dimensional space with no a priori constraints, due to the formation of porous transport walls, and represent a highly complex and novel non-linear behavior. The analysis is numerically carried out as a function of a control parameter showing distinct regimes: static pattern formation, dynamic excitable networks formation, intermittency and chaos. A statistical analysis is drawn to determine the control parameter ranges for the various behaviors to appear. The model and the results shown in this work are expected to contribute to the field of artificial life.

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来源期刊
Theory in Biosciences
Theory in Biosciences 生物-生物学
CiteScore
2.70
自引率
9.10%
发文量
21
审稿时长
3 months
期刊介绍: Theory in Biosciences focuses on new concepts in theoretical biology. It also includes analytical and modelling approaches as well as philosophical and historical issues. Central topics are: Artificial Life; Bioinformatics with a focus on novel methods, phenomena, and interpretations; Bioinspired Modeling; Complexity, Robustness, and Resilience; Embodied Cognition; Evolutionary Biology; Evo-Devo; Game Theoretic Modeling; Genetics; History of Biology; Language Evolution; Mathematical Biology; Origin of Life; Philosophy of Biology; Population Biology; Systems Biology; Theoretical Ecology; Theoretical Molecular Biology; Theoretical Neuroscience & Cognition.
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