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
3.3 KiB
E11 — the dynamic Lamarckian society: the vertical claim (C3)
Claim tested. The culmination. Everything before was a single operator; the society's load-bearing, un-preempted claim is that composing them makes general capability climb over generations while specialties are re-earned, and that every operator is necessary — remove one and it breaks. This is blueprint C3, the "vertical."
Setup. A finite population of N=60 agents (genotypes of L=12 biallelic loci) evolves on a
rugged Kauffman NK landscape (K=8) that is reality. Each generation composes: grounding,
directed recombination (sex), quality-diversity selection, and mutation. Grounding is made
load-bearing by the consensus-conformity (self-consumption) mechanism — selection acts on
g·true_fitness + (1−g)·conformity, where conformity = agreement with the population's own consensus,
so at g=0 the society optimises fitting-the-crowd rather than reality. A 4-arm ablation, 12
replicate landscapes, 80 generations.
Symbols
- agent = a model (a genotype); reality = the NK fitness landscape; grounding
g= share of the selection signal that is real fitness vs conformity. - directed sex = recombine many parents + keep the fittest offspring (E10). quality-diversity = select for capability and novelty, so specialties persist.
- conformity − true fitness = how far the population's mutual agreement exceeds its real capability (the self-consumption "delusion" signature).
The three panels (over generations)
- The vertical climb. Best real capability: the full society (green) climbs to the global
optimum (≈0.78 of 0.79), while no_grounding (red) collapses to a fit-looking but poor
consensus (0.48).
no_sexandno_diversityplateau below the full society. - Specialties maintained. Population diversity: the full society explores longest (diversity
decays slowly as it searches), while every ablation collapses diversity fast —
no_groundingalmost immediately. - Self-consumption signature. Conformity minus true fitness: largest for
no_grounding— the population strongly agrees while being wrong, the signature of training on its own consensus.
Takeaway — every operator is load-bearing
- full → climbs to the optimum with diversity maintained. The vertical claim.
- no_grounding → self-consumption collapse to an unfit consensus (train on the crowd → regress to a confident, wrong mean).
- no_sex → can't recombine complementary specialists to escape local optima → plateaus below full.
- no_diversity (greedy) → collapses diversity fastest, gets stuck at a worse local optimum.
This integrates the whole study — E1–E6 (collapse/grounding/selection), the learning kernel, and E7–E10 (sexual transmission) — into one system, and shows the Lamarckian society needs all of grounding + directed sex + diversity to climb without collapsing. On a rugged landscape you need diversity to explore basins, sex to recombine them, and grounding to select on reality; remove any and you fail differently. Falsifier (not triggered): if any ablation had matched the full society, or the full society had failed to exceed every ablation, the integration claim would fail.