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Updated: Jun 28, 2026
04:52
Following the Dynamics of Structural Variants in Experimentally Evolved Populations
Published on: February 3, 2023
From episodes to populations: evolutionary explanation requires a constructive epistemology
1Emdan Research, New York, USA. dan@danadler.com.
Theory in Biosciences = Theorie in Den Biowissenschaften
|June 26, 2026
Summary
This study distinguishes law-based and evolutionary sciences by epistemic regimes, not subject matter. It introduces Stability-Driven Assembly (SDA) to model evolutionary dynamics, highlighting population memory as key to open-ended processes.
Area of Science:
- Theoretical Biology
- Philosophy of Science
- Complex Systems
Background:
- Scientific disciplines are broadly categorized into law-based sciences and historical sciences.
- This division is often attributed to differences in subject matter, but this work posits it stems from distinct epistemic regimes.
- Law-based sciences utilize episodic closure, idealizing systems to maintain consistent rules, which aids prediction but obscures evolutionary dynamics.
Purpose of the Study:
- To formally distinguish between law-based and evolutionary scientific approaches.
- To introduce a novel framework, Stability-Driven Assembly (SDA), for modeling evolutionary dynamics.
- To develop a unified taxonomy of scientific inquiry, including formal possibility and constructive potential.
Main Methods:
- Formalization of scientific regimes using λ-calculus to represent compositional objects.
- Development of the Stability-Driven Assembly (SDA) framework, a minimal non-equilibrium model.
- Analysis of differential persistence and population-level dynamics in the absence of genes or replication.
Main Results:
- Episodic science involves isolated λ-reductions, while evolutionary science studies populations of λ-instantiations with self-modifying dynamics.
- The SDA framework demonstrates how population feedback reshapes dynamics, leading to irreducibly sequential and self-modifying processes.
- A four-quadrant taxonomy is proposed, locating episodic science, evolutionary science, formal possibility, and constructive potential.
Conclusions:
- Population-level memory is identified as the structural element transforming law-governed episodes into open-ended evolutionary processes.
- The "No Free Telos" constraint is derived, stating prediction costs in constructive systems cannot be reduced below simulation costs.
- This framework bridges episodic and historical sciences by focusing on the emergent properties of evolving systems.
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