从进化动力学的角度看神经网络。

IF 2 4区 生物学 Q2 BIOLOGY Biosystems Pub Date : 2025-01-01 DOI:10.1016/j.biosystems.2024.105386
Dan C Baciu
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引用次数: 0

摘要

本文通过进化动力学的视角重新审视了人工神经网络(nn)。神经网络的两个最重要的特征反映了进化动力学的两个最一般的过程。这种重叠可以作为神经网络和进化动力学之间的一个新的和强大的联系,它包含了一个已经建立了几个世纪的知识体系,并已扩展到激发跨广泛学科的应用。因此,神经网络也应该适用于相同范围的学科——也就是说,比最初设想的要广泛得多。文章的结论是基于与进化动力学的新联系,对神经网络动力学提出了一些开放的问题。
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Neural networks through the lens of evolutionary dynamics.

This article revisits Artificial Neural Networks (NNs) through the lens of Evolutionary Dynamics. The two most important features of NNs are shown to reflect the two most general processes of Evolutionary Dynamics. This overlap may serve as a new and powerful connection between NNs and Evolutionary Dynamics, which encompasses a body of knowledge that has been built over multiple centuries and has been expanded to inspire applications across a vast range of disciplines. Consequently, NNs should also be applicable across the same range of disciplines-that is, much more broadly than initially envisioned. The article concludes by opening questions about NN dynamics, based on the new connection to Evolutionary Dynamics.

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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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