Giorgio Gilestro
6f8cef1ac5
Removed from main (all preserved on the dev branch): the arXiv build and
its sources, design documents (blueprint, results summary, review responses,
essay drafts), tasks/ and CLAUDE.md, the cover letter and reference tooling,
two unused manuscript figures, and every experiment that feeds no figure or
number in the paper: the collapse null, the sexual-vs-asexual lineage, the
NK speciation variant, the 0.5B single-seed LLM prototypes, the compose and
society experiments with their calibration and pilot runs, and their
configs, runners, tests, figure scripts and PBS jobs. Their result bundles
are moved to results/_archive/ (ignored) so the parquets stay on disk.
Also: plot_llm_speciation reads the s{seed}/ layout; the mating-breadth
plot writes under its bundle name; Makefile targets reduced to the kept
experiments; REPRODUCING.md and README point to dev for the rest.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
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| figS10_rugged_landscapes.pdf | ||
| figS10_rugged_landscapes.png | ||
| manifest.json | ||
| README.md | ||
| resolved_config.yaml | ||
E9 — landscape robustness: when recombination helps, and the outbreeding-depression risk
Claim tested. E8 showed sexual recombination assembling super-parent offspring — but on an additive landscape, where recombination trivially helps. The honest, credibility-critical question (the classic "why sex?" problem): does the benefit survive epistasis, or does merging entangled models break them?
Setup. Parents are local optima ("trained models") of a Kauffman NK landscape (L=12),
whose ruggedness K (epistatic interactions per locus) is swept together with the recombination
rate. K=0 is additive/smooth; larger K is rugged (co-adapted allele blocks, many local optima).
Fitness ∈ [0,1]. 24 replicate landscapes; 200 offspring per point.
Symbols
- NK landscape — tunable-ruggedness fitness landscape;
K= epistasis (0 = additive, high = rugged). - recombination rate — per-gap crossover probability (0 = clonal / copy a parent; 0.5 = free recombination, loci independent).
- outbreeding depression — offspring less fit than parents because recombination broke co-adapted allele blocks.
The two panels
- The risk. Mean offspring fitness minus best parent, vs recombination rate, one curve per
ruggedness
K. On the additive landscape (K=0) it's flat at 0; asKgrows the curves plunge negative, and deeper the higher the recombination rate — outbreeding depression, worse the more entangled the skills and the more you mix (K=8, free recombination: ≈ −0.23). - With selection, an optimal rate re-emerges. Best-of-brood fitness (offspring selection) vs
rate per
K, with parents dotted. On rugged landscapes a nonzero intermediate recombination rate is best — enough mixing to find new combinations, not so much that it shatters good blocks.
Takeaway
Recombination is not a free lunch. Merge freely when skills are complementary/additive; merge sparingly — and always select offspring — when they are entangled. This is the celebrated population-genetics result (recombination load / outbreeding depression) reproduced for AI model merging, and it turns the sexual metaphor from a lucky demo into a law with a design rule. The rescue — directed sex with offspring selection — is E10. Falsifier (not triggered): if recombination rate had no effect, or free recombination never underperformed the parents on rugged landscapes, the epistasis caveat would be moot.