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MachineSex/results/figS11_directed_recombination/README.md
Giorgio Gilestro ab3dc10587 Restructure: descriptive tier and experiment names, paper/manuscript 
- 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
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  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
2026-09-13 17:00:40 +01:00

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E10 — directed sex beats biological sex (the distinctly-AI superpower)

Claim tested. E9 showed that on rugged (epistatic) landscapes, blind recombination causes outbreeding depression — offspring worse than parents. Biology is largely stuck with this: two random-mating parents, no way to preview offspring. But an AI is not — it can choose mates, evaluate many recombinant offspring, and keep only the fittest, over rounds, with no two-parent limit. Does this directed sex rescue recombination where blind sex fails?

Setup. Parents are local optima of a Kauffman NK landscape (L=12), swept over ruggedness K. Three strategies compared, all as deployed capability (fitness ∈ [0,1]): best single parent; random sex (blind mating, free recombination, no offspring selection — biology's default); directed sex (iterated recombine-then-select-offspring, rate=0.2, 5 rounds — the AI move). 24 replicate landscapes.

Symbols

  • random sex — blind: random parents, free recombination, take the offspring as they come.
  • directed sex — choose complementary mates + generate many offspring + keep the fittest + repeat; unbounded parents.
  • global optimum — the landscape's best genotype (the ceiling).

The two panels

  1. Capability vs ruggedness. As K grows, random sex (blue) craters (0.66 → 0.51 — deep outbreeding depression), while directed sex (red) tracks the best parent and the global optimum, staying near the ceiling at every ruggedness.
  2. Edge over the best parent. Directed sex stays ≥ 0 (at or above the parents) across all K; random sex falls to ≈ −0.2 (far below). Directed sex converts a catastrophe into a win.

Takeaway

The move biology cannot make — choose your mates, evaluate your offspring before you commit, and recombine as many parents as you like — is exactly what makes AI sexual reproduction robust. Blind merging of entangled models is dangerous; directed merging (generate many candidate merges, keep the best) is safe and can exceed every parent. This is the practical payoff of the sexual-transmission model and the distinctly-AI superpower with no biological analog. Falsifier (not triggered): if directed sex did no better than random sex, or never recovered the best-parent level on rugged landscapes, the "AI beats biology" claim would fail.