Giorgio Gilestro
48181a1c84
Deepen the sexual-reproduction frame before entering the full society, on
the two facets GG chose: landscape robustness and directed recombination.
Adds a Kauffman NK landscape (genotype.nk_fitness, tunable ruggedness),
finite n-parent crossover (genotype.crossover, per-gap recombination rate),
and hill-climb (parents = local optima = trained models).
E9 (recomb_landscape) -- the "why sex?" test: E8's dramatic super-parent
result used an ADDITIVE landscape. On rugged/epistatic landscapes, blindly
recombining local optima causes OUTBREEDING DEPRESSION -- offspring fall
below the parents, worse with both ruggedness and recombination rate (K=8,
free recomb: ~ -0.23), and the optimal recombination rate shrinks as
ruggedness grows. Design rule: merge freely when skills are complementary/
additive; sparingly (and with selection) when entangled.
E10 (directed_sex) -- directed sex beats biological sex: biology is stuck
with 2 random-mating parents and no offspring preview; an AI can choose
complementary mates, evaluate many recombinant offspring, keep the fittest,
and use unbounded parents (iterated recombine-then-select). Random
("biological") sex craters with ruggedness (0.66->0.51); directed sex
tracks/exceeds the best parent at every ruggedness -- converting the
outbreeding-depression catastrophe into a win. No biological analog.
Complete sexual-transmission picture: dramatic super-parent offspring when
skills are complementary (E8); outbreeding-depression risk when entangled
(E9); directed sex resolves the risk (E10). configs/layer1/{E9,E10}.yaml,
figures/plot_{E9,E10}.py, READMEs, +5 tests (117 green).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2.4 KiB
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
- Capability vs ruggedness. As
Kgrows, 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. - 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.