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homemaker-layout/experiments/bakeoff_harbor.json
Bruno Postle 0e5e607c4f Swap inner loop default from CMA-ES to Nelder-Mead (homemaker-py-d6d) 
Bakeoff with native fitness shows NM wins at all DOF sizes: +9% at
child_budget=80 for programme-house (6-7 DOF), and decisively at
harbor-house scale (35-40 DOF) where CMA-ES exhausts its convergence
detector after ~3 generations (46 evals) and adds failures on 12/15
runs.  NM uses the full budget, is parameter-free, and has zero new
failures across all test cases.

- Add nm_search() to innerloop.py; change optimise() default to "nm"
- Add nm_search to parametrised test cases
- Add bakeoff_native.py and bakeoff_harbor.py experiments with results

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-14 08:51:22 +01:00

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