Bruno Postle
d08d15e4d7
Driving equal-offset cut ratios with Nelder-Mead against the REAL oracle fitness (full objective, no proxy) improves all three test candidates with zero new failures: 2f45907 (best evolved) 0.012617 -> 0.015684 x1.24 (2->2 fails) candidate-002 0.007375 -> 0.012319 x1.67 (2->2 fails) c964435 (baseline) 0.003667 -> 0.005836 x1.59 (3->3 fails) Headroom widens on weaker designs. The EA under-optimises geometry by 24-67% even on its best result. This validates a full-fitness geometry inner loop (NOT the earlier area-proxy solver) and motivates a memetic architecture: topology search outside, full-objective geometry optimise inside, gated on a native Python fitness (oracle at ~3s/call is too slow). |
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| .. | ||
| dump_areas.pl | ||
| dump_areas.py | ||
| optimize_fullfitness.py | ||
| refine_sweep.py | ||
| resolve_ratios.py | ||
| sweep_failtypes.py | ||