跨越非生命和生命集体的信息架构。

IF 1.3 4区 生物学 Q3 BIOLOGY Theory in Biosciences Pub Date : 2021-11-01 Epub Date: 2021-02-02 DOI:10.1007/s12064-020-00331-5
Hyunju Kim, Gabriele Valentini, Jake Hanson, Sara Imari Walker
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引用次数: 5

摘要

集体行为被广泛认为是生命和智能系统的标志性属性。然而,许多已知的例子表明,没有生命的简单物理系统也表现出集体行为,这促使人们经常采用简单的物理模型来解释有生命的集体行为。为了理解在活生生的例子中发生的集体行为,重要的是要确定非生物系统和生命系统的集体行为是否存在根本差异,以及在解释生物现象时,可以从更简单的物理例子中建立的直觉的局限性。在这里,我们提出了一个框架,将非生物和生物集体作为一个基于其信息架构的连续体进行比较:也就是说,信息是如何在不同的自由度上存储和处理的。我们从信息论的角度回顾了集体现象的不同例子,并对基于其信息结构量化生活集体行为的未来方向提出了看法。
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Informational architecture across non-living and living collectives.

Collective behavior is widely regarded as a hallmark property of living and intelligent systems. Yet, many examples are known of simple physical systems that are not alive, which nonetheless display collective behavior too, prompting simple physical models to often be adopted to explain living collective behaviors. To understand collective behavior as it occurs in living examples, it is important to determine whether or not there exist fundamental differences in how non-living and living systems act collectively, as well as the limits of the intuition that can be built from simpler, physical examples in explaining biological phenomenon. Here, we propose a framework for comparing non-living and living collectives as a continuum based on their information architecture: that is, how information is stored and processed across different degrees of freedom. We review diverse examples of collective phenomena, characterized from an information-theoretic perspective, and offer views on future directions for quantifying living collective behaviors based on their informational structure.

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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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