Giorgio Gilestro
ab3dc10587
- paper/pnas -> paper/manuscript (venue-neutral)
- configs/layer1 -> configs/inheritance, src/knowledge -> src/inheritance
(imported as `inheritance`), make layer1 -> make inheritance; layer2 alias dropped
- inheritance and trained-network bundles named after the manuscript figure
they feed (fig2_grounding_sweep, figS3_rebaselining, ...), or descriptively
where they feed none; configs keep their `experiment:` value so parquet
hashes are unchanged, only output.dir moves
- figure scripts, SI figure sources, notebooks, REPRODUCING.md, README and the
SI Methods/tables updated; make clean no longer deletes tracked manifests;
reproduce.sh hashes the s{seed}/ layouts too
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
22 lines
954 B
YAML
22 lines
954 B
YAML
experiment: E12_nk
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kind: speciation
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seed: 12
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n_replicates: 15
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# E12 (NK variant) — the EPISTASIS WEDGE, the paper's distinct falsifiable claim: at matched divergence,
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# mergeability is governed by the EPISTASIS (ruggedness K) of the capability landscape, not by divergence
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# alone (every existing ML merge predictor is a divergence measure). Parents are LOCAL OPTIMA reached by
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# hill-climbing a Kauffman NK landscape from random starts; recombining them exposes broken co-adapted
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# blocks. As K rises, recombining two adapted parents flips from a gain (offspring above the worse parent)
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# to outbreeding depression (offspring below it). K=0 (additive) is the no-isolation control.
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speciation:
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landscape: nk
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L: 16
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K: [0, 2, 4, 6, 8, 10] # ruggedness / epistasis knob
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n_pairs: 40 # random parent-pairs (local optima) aggregated per landscape
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recomb_rate: 0.5
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n_offspring: 200
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output:
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dir: results/speciation_bdm_nk
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