- 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
24 lines
1.4 KiB
Markdown
24 lines
1.4 KiB
Markdown
# Simulations
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Runnable implementations of the models in `models/`. Each simulation names the
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model version it implements.
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| Directory | Model | Entry points |
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|-----------|-------|--------------|
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| `gadm02/` | GADM-0.2 (`models/GADM-0.2.md`) | `run_scenarios.py`, `sensitivity.py`, `gsa.py`, `test_gadm02.py` |
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| `gadm02/gadm03.py` | GADM-0.3: power channels, wealth, attention (`models/GADM-0.3.md`) | `power_channels.py`, `wealth.py`, `organism_grid.py`, `test_gadm03.py` |
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| `gadm02/gadm03c.py` | GADM-0.3 with life-cycle cohorts (`models/GADM-0.3.md` § 5) | `life_cycle.py`, `test_gadm03c.py` |
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| `gadm02/gadm04.py` | GADM-0.4 (in development): durable capability (`models/GADM-0.4.md`) | `life_cycle.py --model gadm04`, `robustness.py`, `test_gadm04.py` |
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Python 3.10+, standard library only. Use `python3 -B` after quick edits: a stale
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bytecode cache can mask same-size changes made within the same second.
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```bash
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python3 -m unittest discover -s simulations/gadm02 # tests
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cd simulations/gadm02 && python3 run_scenarios.py # → results/summary.md + CSVs
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cd simulations/gadm02 && python3 sensitivity.py # → results/sensitivity.md
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cd simulations/gadm02 && python3 gsa.py # → results/gsa.md (~5 min; --quick)
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```
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Results under `results/` are committed so that model documents can cite them.
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Regenerate them after any change to the model or the scenarios.
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