The Information Dynamics of Decline: Modeling Senescence as a Life-History Trajectory in the DECC Phase Space

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Autor principal: Kevin Fathi
Formato: Recurso digital
Lenguaje:inglés
Publicado: Zenodo 2025
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author Kevin Fathi
author_facet Kevin Fathi
contents <p>This paper introduces a novel theoretical framework for understanding the evolution of senescence, recasting it as an information-dynamic process. We apply the Dynamic Entropy--Complexity Correspondence (DECC) to model an organism's life history. We establish a rigorous foundation by modeling the unfolding of the developmental program over the lifespan as a Continuous-Time Markov Process governed by a Master Equation. From this, we rigorously derive the Age-Dependent Complexity Dynamics Equation (CDE). By weighting the CDE terms by Fisher's reproductive value ($V_{a}$), we transform the problem of life-history evolution into one of optimal control. We demonstrate that the canonical theories of senescence---Disposable Soma (DS), Antagonistic Pleiotropy (AP), and Mutation Accumulation (MA)---emerge as distinct classes of solutions to a single variational problem. The DS theory is shown to be an optimal strategy trading late-life robustness ($\dot{\Delta}<0$) for early-life phenotypic expression ($\dot{H}(X)>0$). AP represents a constrained trajectory, while MA arises from vanishing selective pressure ($V_{a}\rightarrow 0$). This synthesis provides a unified, mathematically rigorous foundation for senescence, explaining it as an evolved, optimal, and information-theoretically constrained strategy.</p>
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spellingShingle The Information Dynamics of Decline: Modeling Senescence as a Life-History Trajectory in the DECC Phase Space
Kevin Fathi
Bateson Game
Senescence
Biological Aging
Evolutionary Game Theory
Gregory Bateson
Double Bind
Recursive Systems
Strategic Ambiguity
Logical Types
Systems Biology
Cybernetics
Aging Theory
Inter-level Signaling
Temporal Discounting
<p>This paper introduces a novel theoretical framework for understanding the evolution of senescence, recasting it as an information-dynamic process. We apply the Dynamic Entropy--Complexity Correspondence (DECC) to model an organism's life history. We establish a rigorous foundation by modeling the unfolding of the developmental program over the lifespan as a Continuous-Time Markov Process governed by a Master Equation. From this, we rigorously derive the Age-Dependent Complexity Dynamics Equation (CDE). By weighting the CDE terms by Fisher's reproductive value ($V_{a}$), we transform the problem of life-history evolution into one of optimal control. We demonstrate that the canonical theories of senescence---Disposable Soma (DS), Antagonistic Pleiotropy (AP), and Mutation Accumulation (MA)---emerge as distinct classes of solutions to a single variational problem. The DS theory is shown to be an optimal strategy trading late-life robustness ($\dot{\Delta}<0$) for early-life phenotypic expression ($\dot{H}(X)>0$). AP represents a constrained trajectory, while MA arises from vanishing selective pressure ($V_{a}\rightarrow 0$). This synthesis provides a unified, mathematically rigorous foundation for senescence, explaining it as an evolved, optimal, and information-theoretically constrained strategy.</p>
title The Information Dynamics of Decline: Modeling Senescence as a Life-History Trajectory in the DECC Phase Space
topic Bateson Game
Senescence
Biological Aging
Evolutionary Game Theory
Gregory Bateson
Double Bind
Recursive Systems
Strategic Ambiguity
Logical Types
Systems Biology
Cybernetics
Aging Theory
Inter-level Signaling
Temporal Discounting
url https://doi.org/10.5281/zenodo.17538075