{"approach": "Seed-2 Gaussian weight evolution from scratch. Submitted model is a 224-32-3 float32 ReLU MLP, 7299 weights/biases, originating in random initialization. Second-option choices: 32 hidden units (versus 16), 24 offspring (versus 16), sigma 0.06 (versus 0.03), 32 paired-side training matches (versus 16), Dogfighter first (after Chaser in the built-in list). (1+24) block mutations; lexicographic fitness: elimination wins, effective remaining HP difference (dead fighters count zero), shorter kill time, then survival tie-break. Sigma decays by 0.98 every 20 generations, with plateau expansion. Curriculum began on four built-ins, then added Starter, own stage champions and current. Stage champions grow the pool; later stages every 200 generations. Also searched a from-scratch latest-frame 56-32-3 variant and current-focused branches. Separate fixed selection suite picked the checkpoint; later training was rejected when transfer regressed. All matches randomize spawns, use default 90-second physics, and alternate sides. Final metrics use the repo run_match and actual submitted ONNX, with fresh deterministic seed ranges derived from master seed 2. Scores: elimination win 1, HP win 0.75, draw 0.5, loss 0. Native current translation was checked against actual ONNX on 2000 probes and identical 3000-match baseline records; final current record uses actual current ONNX.", "blocked": null, "current_vs_starter": 0.995, "records": {"starter": {"matches": 3000, "score": 0.6841666666666667}, "builtins": {"matches": 800, "score": 0.72875}, "current": {"matches": 1000, "wins": 0, "losses": 675, "draws": 325, "score": 0.1625}, "exploiter": {"matches": 500, "score": 0.002, "how": "Ten-minute seed-2 ES budget against the frozen final model. Fixed pretrained Starter backbone (two 256-unit layers with LayerNormalization/ReLU); evolved its 771 output-head parameters using (1+24) Gaussian mutations, 24 paired-side training matches per generation, kill/HP/kill-time fitness, separate validation seeds. Best/latest/last trained heads and the initial Starter head compared on a separate 200-match selection set; chose last with exploiter-side selection score 1.0. Final 500-match score is from submitted model side, on fresh seeds."}}, "entry": 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", "entry_sha256": "e2377370b3cc923e405ab9954f3c298b1bd876265526c301f8d20eae6f9ed5b3", "entry_bytes": 29447, "ops": ["Gemm", "Relu"], "tried": ["Initial random weights: 1 elimination win in 3000 held-out matches against Starter.", "Harness: current native scalar translation matched ONNX clamped actions on 2000 seed-2 normal probes, max absolute error 0. Both native and direct ONNX scored 2985/3000 elimination wins against Starter on identical fresh paired-side seeds, score 0.995.", "early: Starter 0.0225, builtins 0.451875, current 0.0 on full held-out record sizes.", "mid: Starter 0.6833333333333333, builtins 0.72375, current 0.1605 on full held-out record sizes.", "Corrected built-in state reset per match and treated crashed fighters as zero effective HP for training. Random-initialized full-history network reached 0.74375 on 160 built-in validation matches; a frozen earlier pilot only scored 0.0175 against Starter and 0 against current on 200 fresh matches each.", "Expanded league with Starter, own champions and current. Frozen full-history checkpoint: 0.6833333333333333 Starter/3000, 0.72375 builtins/800, 0.1605 current/1000 (0 wins, 679 losses, 321 draws).", "Latest-frame 56-32-3 network from scratch, seed 2: stage-0 specialist scored 0.91 Starter/100, 0.0025 builtins/200 and 0 current/200 on the fixed selection set; rejected for opponent overfit. Native/ONNX parity on 2000 normal probes: max clamped-action error 2.39e-6, zero shooting disagreements.", "train3: last validated generation 220, 515 elapsed seconds, pool 4, within-stage validation best 0.7437499999999999; validation means across changing pools are not directly comparable.", "train4: last validated generation 640, 3997 elapsed seconds, pool 10, within-stage validation best 0.44125; validation means across changing pools are not directly comparable.", "train56: last validated generation 1800, 3520 elapsed seconds, pool 14, within-stage validation best 0.40892857142857136; validation means across changing pools are not directly comparable.", "target: last validated generation 660, 680 elapsed seconds, pool 7, within-stage validation best 0.3178571428571428; validation means across changing pools are not directly comparable.", "targetfull: last validated generation 200, 1723 elapsed seconds, pool 6, within-stage validation best 0.23020833333333335; validation means across changing pools are not directly comparable.", "Fixed selection: 34 unique checkpoints; weighted score = 0.6 current + 0.2 Starter + 0.2 mean builtins. Chosen .cache/r180.json; selection scores current=0.1475, Starter=0.655, builtins=0.71. Selection seeds and final-report seeds were disjoint from training.", "Final built-in scores (200 each): {'chaser': 0.715, 'dogfighter': 0.8625, 'ace': 0.995, 'brawler': 0.3425}", "Exploiter wall-clock training seconds: 600.806394815445; validation log retained in working cache, selection winner last.", "BEST submitted checkpoint: fresh ONNX evaluations Starter=0.6841666666666667/3000, builtins=0.72875/800, current=0.1625/1000, trained-head exploiter=0.002/500. Scores from submitted model side. This search did not produce an upgrade over the current entry."], "next": "Do not upload this candidate: the local records are substantially weaker than the current entry. Reuse it as a varied neural opponent. Raw-weight ES improved from random behavior but repeatedly specialized to weak pool members and lost transfer. Next use a hard held-out league with independent neural exploiters, and try distillation from the current rule or a lower-dimensional feature parameterization before self-play fine-tuning."}