Core Architecture – The Evolutionary Loop

At the heart of Synthetic Darwin is a recursive loop:

Generation n
┌───────────────────────────────┐
│ Population  Pₙ  (|P| = N)      │
└──────────────┬────────────────┘
               │ evaluate fitness  ƒ(x)
               ▼
rank / roulette / tournament-selection → Parents
               │
        ┌────────┴─────────┐
        │ crossover  χ      │  (single-, two-, or uniform-point)
        │ mutation   μ       │  (param tweak, prompt splice, code diff)
        └────────┬─────────┘
               ▼
           Offspring  Ōₙ
               │   elitism ε% of Pₙ
               ▼
Pₙ₊₁  ←  ε · best(Pₙ)  ∪  (N-ε) · Ōₙ
               │
stop if  Δfitness < τ  or  n ≥ n_max

Each generation aims to create better successors.