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From inert baseline to auditable life-like behavior

To Wake a Stone with Six Birds: A Life is A Theory

Applies the emergence calculus to life: starts from a calibrated zero, switches on drive, and tests for life-like properties across particle and neural substrates, with every claim backed by a matched control.

Preprint - v1 Not peer reviewed Published Jan 27, 2026 Zenodo DOI

Plain-language overview

This paper applies the emergence calculus to the question "what makes something life-like?" It builds two concrete systems (a particle simulation and a neural network) and follows a strict discipline: first confirm that all measurements read zero when nothing is driven, then switch on energy input and show that life-like signals (maintenance, repair, pattern formation) rise above the baseline. Every claim comes with a side-by-side control, not rhetoric.

"To wake a stone" means taking a system from an inert, calibrated zero baseline to one that sustains directed behavior and pays maintenance costs, while carefully distinguishing real arrows of time from artifacts of scheduling.

- Ioannis Tsiokos

At a glance

Start from a clean zero

Before claiming any life-like signal, first turn off all drive and scheduling. Confirm that every measurement reads approximately zero. This prevents false positives.

Drive separates cleanly from null

When the energy-input channel is switched on, measurements rise clearly above the zero baseline. This holds on both the particle and neural substrates.

Order effects are diagnostic, not proof

Changing the order of operations (protocol) visibly changes coarse statistics, but this alone does not prove a real arrow of time. That requires a separate directionality test.

Life-like competencies, bounded

Maintenance, repair, and higher-level pattern detection are demonstrated with explicit controls. No claim of autonomous open-ended evolution is made.

Audit-first loop

Null, drive, refinement

Two substrates, the same three-step logic: calibrate to zero, test for drive, then check higher-level structure.

Zero baseline

Null calibration

With scheduling and energy drive both off, the system still moves but all directionality measurements read approximately zero. This is the clean baseline.

Directionality test

Audited drive channel

A controllable energy-input channel is switched on. Directionality measurements rise above zero under matched comparison with the null. This confirms the signal is real, not noise.

Lens extension

Refined lenses

Higher-level patterns (repeating motifs, stable vocabularies, decodable signals) are checked with explicit pass/fail gates and "shift the baseline" controls.

Highlighted results

What the paper establishes

Every claim is backed by a side-by-side control comparison, not by rhetoric.

Null regime validation

Both substrates (particle and neural) are calibrated so all directionality measurements hover near zero when drive is off. This rules out instrumentation artifacts.

Drive separability across substrates

Turning on the energy-input channel raises directionality measurements above the null baseline on both substrates, confirming the drive is a genuinely separate signal.

Protocol order effects are documented

Changing the scheduling order visibly shifts coarse statistics under matched comparison, but this is reported as a diagnostic, not treated as proof of an arrow of time.

Maintenance and higher-level structure

Repair, hazard response, stable pattern inventories, and intervention-based decoding all pass explicit pass/fail gates with matched controls.

Methods & reproducibility

How the results are supported

  • Two concrete implementations: a particle-based substrate and a neural/meta-layer substrate.
  • Side-by-side comparisons: every "drive on" result is shown next to its "drive off" control.
  • Approximate directionality measurements with strict zero-baseline calibration and pass/fail gates.
  • Each higher-level claim (patterns, vocabularies, decoding) is tested against a shifted baseline to rule out artifacts.
  • A machine-readable claim ledger maps every reported result to its underlying experimental files.

Sanity checks

  • - With scheduling and drive both off, all directionality measurements are statistically consistent with zero.
  • - Order-of-operations effects are reported only as diagnostics; a real arrow of time requires a separate directionality test.
  • - Failed early attempts (e.g., premature semantics claims) are reported as constraints, not partial wins.

Media-ready

Figures & demos

Both experiment repositories include deterministic scripts that regenerate the audit tables and summary figures. They are designed so journalists and readers can reproduce the reported checks end-to-end.

- Zero-baseline calibration and drive-vs-null separation checks

- Order-of-operations diagnostics under matched comparison

- Maintenance, hazard response, and higher-level pattern summaries

Regenerate figures from code

Limitations & scope

Read-this-first caveats

  • No exact mathematical directionality audit; reported signals are approximate proxies.
  • No measured stability score (idempotence defect) for the closure; stability is demonstrated operationally.
  • No arrow-of-time claims from scheduling order alone. Order effects are reported as diagnostics, not proofs.
  • No claim of autonomous open-ended evolution under a fixed set of rules.
  • No formal proof that the higher-level patterns are strictly beyond the base-level vocabulary.

Citation

How to cite

Ioannis Tsiokos (2026). To Wake a Stone with Six Birds: A Life is A Theory. Zenodo. https://doi.org/10.5281/zenodo.18394536

BibTeX

@misc{tsiokos2026wake,
  title = {To Wake a Stone with Six Birds: A Life is A Theory},
  author = {Tsiokos, Ioannis},
  year = {2026},
  publisher = {Zenodo},
  doi = {10.5281/zenodo.18394536},
  url = {https://doi.org/10.5281/zenodo.18394536}
}

Press & contact

Talk to the author

For media inquiries, figures, or walkthroughs of the audit-first workflow, reach out directly.

Ioannis Tsiokos

ioannis@automorph.io

Corresponding author - Press contact

Questions welcome about the zero-baseline method, drive separation, and higher-level pattern claims.