How Information Evolves: Stability-Driven Assembly and the Emergence of a Natural Genetic Algorithm

Dan Adler

arxiv: 2601.17061 · v2 · submitted 2026-01-22 · 🧬 q-bio.PE · cs.NE· nlin.AO

How Information Evolves: Stability-Driven Assembly and the Emergence of a Natural Genetic Algorithm

Dan Adler This is my paper

Pith reviewed 2026-05-16 12:02 UTC · model grok-4.3

classification 🧬 q-bio.PE cs.NEnlin.AO

keywords stability-driven assemblynatural genetic algorithmchemical evolutionnon-equilibrium dynamicsemergent selectionSMILES recombination

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The pith

Longer-persisting chemical assemblies become more frequent, implementing a natural genetic algorithm driven only by stability.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper shows that information can evolve through physical non-equilibrium dynamics even without genes, replication, or any predefined fitness function. Stability-Driven Assembly combines stochastic assembly of fragments with differential persistence so that longer-lived motifs appear more often and join more future combinations. This feedback loop automatically produces fitness-proportional sampling and yields evolutionary search signatures such as scaffold dominance, sustained novelty, and entropy reduction when applied to SMILES fragments with recombination and mutation.

Core claim

Assemblies that persist longer become more frequent and therefore participate more in subsequent interactions, generating feedback that reshapes the population distribution and implements fitness-proportional sampling, realizing evolution as a natural emergent genetic algorithm driven solely by stability.

What carries the argument

Stability-Driven Assembly (SDA) using a heuristic stability function on stochastic recombination and mutation within chemical symbol space.

If this is right

Populations shift toward longer-lived motifs without external fitness or replication rules.
Scaffold-level dominance and open-ended novelty emerge from persistence bias alone.
Persistence-driven selection can precede genetic replication in an evolutionary ladder.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

The same persistence mechanism could generate evolutionary-like behavior in non-chemical domains such as molecular networks or social structures.
Varying the stability heuristic across runs would test how robust the emergent dynamics are to different persistence measures.

Load-bearing premise

A heuristic stability function combined with stochastic assembly and differential persistence is sufficient to produce sustained evolutionary dynamics without any external fitness definition or replication rule.

What would settle it

A simulation in which every assembly is assigned identical persistence times shows no population reshaping toward longer-lived motifs and no evolutionary hallmarks.

read the original abstract

Information can evolve as a physical consequence of non-equilibrium dynamics, even in the absence of genes, replication, or predefined fitness functions. We present Stability-Driven Assembly (SDA), a framework in which stochastic assembly combined with differential persistence biases populations toward longer-lived motifs. Assemblies that persist longer become more frequent and are therefore more likely to participate in subsequent interactions, generating feedback that reshapes the population distribution and implements fitness-proportional sampling, realizing evolution as a natural, emergent genetic algorithm (SDA/GA) driven solely by stability. We apply SDA/GA to chemical symbol space using SMILES fragments with recombination, mutation, and a heuristic stability function. Simulations show hallmark features of evolutionary search, including scaffold-level dominance, sustained novelty, and entropy reduction, yielding open-ended dynamics absent from equilibrium models with fixed transition rates. These results motivate an evolutionary ladder hypothesis where persistence-driven selection precedes genetic replication.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Desk Editor's Note private letter to a colleague

The paper sketches a physical route to GA-like evolution from persistence biases alone, but the simulations rest on an external heuristic stability function that probably supplies the selection pressure.

read the letter

The central claim is that stochastic assembly plus differential persistence can generate fitness-proportional sampling and open-ended evolutionary search without genes or predefined fitness. The authors call this Stability-Driven Assembly (SDA/GA) and test it on SMILES fragments with recombination and mutation operators. Simulations are said to produce scaffold dominance, sustained novelty, and entropy reduction, which they contrast with equilibrium models. That framing is new enough to stand out from standard genetic-algorithm work; it tries to derive the selection step directly from longer-lived motifs becoming more frequent in subsequent interactions. The evolutionary-ladder hypothesis that follows is a clean conceptual move for origins-of-life thinking. The paper does a decent job laying out the feedback loop in plain terms and naming the right signatures to watch for in the output. The soft spot is exactly the one flagged in the stress-test note. The stability function is heuristic rather than derived from the non-equilibrium assembly rules, and the model already includes explicit recombination and mutation. That combination makes it hard to know whether the reported dynamics are a general consequence of persistence or an artifact of how the heuristic was written. The abstract supplies no parameter values, error bars, or control runs, so the quantitative support remains thin even if the full text adds some. A reader who wants to see emergent GA behavior without any hand-tuned stability measure will come away unsatisfied. This is worth sending to peer review for people working on prebiotic chemistry or open-ended artificial life. The idea is distinct and the target audience is clear, but the authors will need to show that the results survive changes to the stability rule and provide the missing numbers before the central claim can be taken as demonstrated.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes Stability-Driven Assembly (SDA) as a framework in which stochastic assembly combined with differential persistence of longer-lived motifs generates feedback that reshapes population distributions, implementing fitness-proportional sampling and realizing evolution as an emergent genetic algorithm (SDA/GA) driven solely by stability, without genes, replication, or predefined fitness functions. Applied to SMILES fragments with recombination, mutation, and a heuristic stability function, the simulations are claimed to exhibit scaffold-level dominance, sustained novelty, and entropy reduction, supporting an evolutionary ladder hypothesis where persistence-driven selection precedes genetic replication.

Significance. If substantiated with quantitative evidence and a stability function derived from the assembly rules, the framework would offer a significant contribution by providing a physical mechanism for the emergence of evolutionary search dynamics from non-equilibrium processes alone, with implications for origins-of-life research and the foundations of natural computation.

major comments (2)

[Abstract] Abstract: the claim that simulations exhibit scaffold-level dominance, sustained novelty, and entropy reduction is asserted without any quantitative results, error bars, parameter values, or derivation steps, leaving the central empirical support for the SDA/GA dynamics absent from the presented evidence.
[Methods (stability function)] Stability function definition (methods section): the function is described as heuristic, yet the central claim requires that the observed GA-like behavior (population reshaping, fitness-proportional sampling, entropy reduction) arises independently from the stochastic assembly rules and differential persistence alone. Because the heuristic is externally chosen rather than derived from the non-equilibrium assembly dynamics, the results may reduce to an artifact of that specific choice rather than a general physical consequence.

minor comments (2)

[Abstract] The acronym SDA/GA is introduced in the abstract without an explicit prior definition, which reduces clarity for readers.
[Methods] Ensure the exact mathematical form of the heuristic stability function, all simulation parameters, and the precise recombination/mutation operators are stated explicitly to permit independent reproduction.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive report and the opportunity to improve the manuscript. We address each major comment below, indicating planned revisions where appropriate.

read point-by-point responses

Referee: [Abstract] Abstract: the claim that simulations exhibit scaffold-level dominance, sustained novelty, and entropy reduction is asserted without any quantitative results, error bars, parameter values, or derivation steps, leaving the central empirical support for the SDA/GA dynamics absent from the presented evidence.

Authors: We agree that the abstract would benefit from explicit quantitative support. The full manuscript contains these results (entropy reduction with standard deviations across 50 runs, parameter tables, and derivation of the population-reshaping dynamics from the master equation), but the abstract summarizes them only qualitatively. In revision we will add representative quantitative statements to the abstract, including measured entropy drop, scaffold dominance fractions, and key parameter values, while preserving the abstract's length constraints. revision: yes
Referee: [Methods (stability function)] Stability function definition (methods section): the function is described as heuristic, yet the central claim requires that the observed GA-like behavior (population reshaping, fitness-proportional sampling, entropy reduction) arises independently from the stochastic assembly rules and differential persistence alone. Because the heuristic is externally chosen rather than derived from the non-equilibrium assembly dynamics, the results may reduce to an artifact of that specific choice rather than a general physical consequence.

Authors: The stability function is indeed introduced heuristically for the SMILES application, but the core SDA mechanism—differential persistence biasing subsequent assembly probabilities—operates independently of its specific functional form. The population reshaping follows directly from the non-equilibrium rate equations once any monotonic persistence measure is supplied. In revision we will (i) derive an explicit stability proxy from the assembly rules themselves (collision lifetimes and bond energies), (ii) prove that the GA-like sampling emerges for any strictly increasing persistence function, and (iii) add robustness checks with two alternative stability definitions to confirm the dynamics are not artifacts of the chosen heuristic. revision: yes

Circularity Check

1 steps flagged

Heuristic stability function encodes selection criteria, rendering emergent GA dynamics by construction rather than from assembly rules alone

specific steps

fitted input called prediction [Abstract]
"We apply SDA/GA to chemical symbol space using SMILES fragments with recombination, mutation, and a heuristic stability function. Simulations show hallmark features of evolutionary search, including scaffold-level dominance, sustained novelty, and entropy reduction, yielding open-ended dynamics absent from equilibrium models with fixed transition rates."

The paper claims the dynamics realize a natural genetic algorithm driven solely by stability from stochastic assembly and differential persistence. However, it introduces an externally chosen heuristic stability function as input, which directly determines the persistence bias and thus the population reshaping. The observed evolutionary search features are therefore consequences of this heuristic choice rather than independent predictions from the assembly rules.

full rationale

The central derivation asserts that feedback from differential persistence implements fitness-proportional sampling without external fitness definitions. Yet the model relies on a heuristic stability function applied to SMILES fragments, which functions as a predefined selection criterion. This makes the emergence of GA-like behavior dependent on the specific form of the heuristic, reducing the claim to a fitted input presented as an emergent result. No independent derivation of the stability function from non-equilibrium dynamics is provided, leading to partial circularity in the load-bearing step.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 1 invented entities

The central claim rests on the unproven premise that differential persistence alone generates fitness-proportional sampling; the stability function is introduced as a heuristic without independent derivation.

free parameters (1)

heuristic stability function
Used to score SMILES fragments in the simulations; its specific form is not derived from first principles.

axioms (1)

domain assumption Non-equilibrium stochastic assembly produces differential persistence that biases population statistics.
Invoked throughout the framework description as the driver of the feedback loop.

invented entities (1)

Stability-Driven Assembly (SDA) no independent evidence
purpose: Framework that turns persistence into evolutionary selection without replication.
Newly defined construct whose behavior is demonstrated only via the described simulations.

pith-pipeline@v0.9.0 · 5452 in / 1335 out tokens · 29660 ms · 2026-05-16T12:02:48.116835+00:00 · methodology

discussion (0)

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

IndisputableMonolith/Cost/FunctionalEquation.lean washburn_uniqueness_aczel unclear

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unclear
Relation between the paper passage and the cited Recognition theorem.

stability values were assigned to patterns according to the function: S(p) = 100 if p = ABCABA, 50 if p ∈ {ABA, ABC}, ... (Eq. 11); g(p) = 5 + 0.8 HA(p) + ... clipped to [1,40] (Eqs. 12-13)
IndisputableMonolith/Foundation/RealityFromDistinction.lean reality_from_one_distinction unclear

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unclear
Relation between the paper passage and the cited Recognition theorem.

SDA dynamics ... persistence imbalances bias the accumulation of structure ... implements fitness-proportional sampling

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supports: The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends: The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses: The paper appears to rely on the theorem as machinery.
contradicts: The paper's claim conflicts with a theorem or certificate in the canon.
unclear: Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.