Article
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Entropic Dynamics in a Theoretical Framework for Biosystems
Version 1
: Received: 14 February 2023 / Approved: 22 February 2023 / Online: 22 February 2023 (15:32:36 CET)
A peer-reviewed article of this Preprint also exists.
Summers, R.L. Entropic Dynamics in a Theoretical Framework for Biosystems. Entropy 2023, 25, 528. Summers, R.L. Entropic Dynamics in a Theoretical Framework for Biosystems. Entropy 2023, 25, 528.
Abstract
Central to an understanding of the physical nature of biosystems is an apprehension of their ability to control entropy dynamics in their environment. To achieve ongoing stability and survival, living systems must adaptively respond to incoming information signals concerning matter and energy perturbations in their biological continuum (biocontinuum). Entropy dynamics for the living system are then determined by the natural drive for reconciliation of these information divergences in the context of the constraints formed by the geometry of the biocontinuum information space. The configuration of this information geometry is determined by the inherent biological structure, processes and adaptive controls that are necessary for the stable functioning of the organism. The trajectory of this adaptive reconciliation process can be described by an information-theoretic formulation of the living system’s procedure for actionable knowledge acquisition that incorporates the axiomatic inference of the Kullback Principle of Minimum Information Discrimination (a derivative of Jaynes’ principle of maximal entropy). Utilizing relative information for entropic inference provides for the incorporation of a background of the adaptive constraints in biosystems within the operations of Fisher biologic replicator dynamics. This mathematical expression for entropic dynamics within the biocontinuum may then serve as a theoretical framework for the general analysis of biological phenomena.
Keywords
entropic dynamics; biosystems; Kullback Principle of Minimum Information Discrimination; biocontinuum; information geometry
Subject
Biology and Life Sciences, Biophysics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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