tegwick
ee7b17da5e
- dO grounded at 0.20/yr (software, R&D capital, AI hardware evidence); investment/learning rescaled so the baseline organism path is unchanged - robustness.py: key readings hold for grounded dO and brackets on channel self-reinforcement and wealth conversion; P3 effect size grows at strong self-reinforcement - models/ParameterGrounding.md: register of grounded / bracketed / assumed / calibrated parameters, open grounding needs Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Assistant: claude-code Assistant-Model: opus Assistant-Process: 1494246@bnt-lap001 Assistant-Session: caf6de6f-f9e4-47ce-a584-49baa271fa4b
115 lines
4.9 KiB
Markdown
115 lines
4.9 KiB
Markdown
<!--
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Created 2026-10-12 under ASSEMBLY-WP-0006. Sections are added as the
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GADM-0.4 tasks are completed. Implemented by simulations/gadm02/gadm04.py;
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the code is the reference if the two ever disagree.
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-->
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# Generative Assembly Dynamics Model — GADM-0.4
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**Status:** in development, exploratory. Implemented so far: durable human
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capability (§ 1, ASSEMBLY-WP-0006-T01), grounded organism depreciation and
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robustness checks (§ 2, T02).
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GADM-0.4 builds on the GADM-0.3 cohort model (`GADM-0.3.md` § 5), which stays
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unchanged and reproducible in `gadm03c.py`. Time unit: one year.
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---
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## 1. Durable human capability (T01)
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### 1.1 Motivation
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GADM-0.3 failed hypothesis L3: an education push reached working-age
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capability after only about 9 years, and weakly. Working-age capability had no
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memory of childhood, because it relaxed to current conditions within about 8
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years.
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### 1.2 Structure
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Each cohort's capability is split into:
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| Component | Formed by | Depreciation (per year) | Carried by ageing |
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|---|---|---|---|
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| **durable D_c** | education in childhood (`hform`, scaled by `edu`, plus commons X); small lifelong formation for adults (`ll`) | 0.01 (children, working age), 0.02 (seniors), 0.04 (very old) | yes |
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| **current C_c** | GADM-0.3 cohort dynamics (learning, mentoring, deskilling, care) | as GADM-0.3 | yes |
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Effective cohort capability: \(H_c = \tfrac12 D_c + \tfrac12 C_c\). Aggregate H,
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which the rest of the model uses, is population-weighted as in GADM-0.3.
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Two couplings:
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- **Learning begets learning:** a cohort's current-capability gains are
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scaled by \(1 + lbl\,(D_c - 0.5)\).
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- **Birth dilution:** newborns enter the children's cohort with no durable
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capability, so the cohort average is diluted at the birth rate (about 1/20
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per year). A first draft omitted this term; durable capability then
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saturated near 0.85, leaving no room for an education effect.
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Initial values: D_c = C_c = GADM-0.3 H_c, so effective capability starts
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identical to GADM-0.3 (unit-tested).
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### 1.3 Results
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Computed at T01, before `dO` was grounded (§ 2). The grounded values differ
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by at most 0.004.
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| | GADM-0.3 cohorts | GADM-0.4 |
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|---|---|---|
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| Baseline VFAC (t = 100) | 0.323 | 0.323 |
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| Generative regime VFAC | 0.656 | 0.661 |
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| L3: education +50 % → final ΔH working age | +0.010 | **+0.032** |
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| L3: years to half of that effect | 9 | **17** (durable part: 21) |
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| L1: ageing + strong mentoring (tg 0.15), ΔH | −0.018 | −0.029 |
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| L1: stable, no mentoring, ΔH | −0.043 | −0.039 |
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Full tables: `simulations/gadm02/results/life_cycle_gadm04.md`.
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### 1.4 Readings
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1. **L3 is now supported.** Education reaches working-age capability with a
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17-year half-time, inside the hypothesised 15–20 years, and with three
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times the effect. The lag comes from cohort turnover (about 2.2 % per year)
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plus slow durable depreciation. The relaxation time is about
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1/(0.01 + 0.022) ≈ 30 years.
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2. **L1 still holds, more weakly.** Mentoring acts on current capability
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only, so its leverage on effective capability halves. An ageing society
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with strong mentoring still loses less than a stable society without it.
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3. **Macro results are almost unchanged.** Durable capability adds memory,
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not level: baseline and generative VFAC move by at most 0.005. Policies on
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education matter mostly beyond a 20-year horizon, which strengthens the
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case for longer simulation horizons in cohort experiments.
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### 1.5 Limitations
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- The split ½ / ½ between durable and current capability is assumed.
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- Children's *current* capability (inherited from GADM-0.3) still has no
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birth dilution. Only the durable component was corrected.
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- `hform` was chosen so that baseline children's durable capability settles
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near 0.6. It has no empirical anchor yet (see T02).
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---
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## 2. Parameter grounding (T02)
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Details and sources: `ParameterGrounding.md`.
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- **Organism depreciation is grounded:** `dO` = 0.20 per year (evidence range
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0.15–0.35, from software, R&D-capital and AI-hardware depreciation), instead
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of 0.06. Investment, learning and seeding are rescaled (×3.33) so the
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baseline organism path is unchanged. The evidence changes the timescale;
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the level of organism capability remains ungrounded.
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- **The key readings are robust** to the grounded `dO` and to brackets on the
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ungrounded channel self-reinforcement (0.15–0.45) and wealth conversion
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(0.02–0.20). One exception: P3's effect size grows to −0.078 at strong
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self-reinforcement.
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- With grounded `dO`: baseline VFAC 0.325, generative regime 0.665. The life-cycle results
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are essentially unchanged: L3 half-time 17 years, final ΔH working age +0.032;
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L1 ΔH −0.028 (ageing, strong mentoring) against −0.038 (stable, none).
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## Reproduce
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```bash
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python3 -B -m unittest discover -s simulations/gadm02
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cd simulations/gadm02 && python3 -B life_cycle.py --model gadm04
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cd simulations/gadm02 && python3 -B robustness.py # T02 robustness checks
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```
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