Стенд-проверка (stage-2) · промт оператора:

(универсальный)

Ответ агента:

{ "worked": true, "confidence": 9, "verdict": "Built a matched projected dissipative residual RNN and compared it with an unconstrained residual RNN on the structurally appropriate built-in dynamics track (controlled pendulum rollout). Across 8 paired seeds, the idea reduced test MSE from 0.00239047 to 0.000338893, with all 8 paired wins and permutation p=0.0081. The trained-model signature confirmed lower perturbation amplification (0.8873 vs 1.0010) and bounded hidden states (maximum absolute value 1.0).", "metrics": { "baseline": "test MSE mean=0.0023904674, std=0.0008984586, per-seed=[0.0016786052,0.0020929552,0.0026723652,0.0044336999,0.0019304326,0.0020707706,0.0013639050,0.0028810054], best lr=0.006, epochs=18", "idea": "test MSE mean=0.0003388932, std=0.0002533149, per-seed=[0.0002524245,0.0001881546,0.0002420832,0.0010012880,0.0002840845,0.0002892777,0.0001796607,0.0002741727], best lr=0.006, epochs=18", "comparison": "delta_mean=-0.0020515742, idea_wins=8/8, permutation_p=0.0081, verdict=idea better (significant)", "mechanism_signature": "baseline perturbation ratio=1.0009678, idea perturbation ratio=0.8872583, idea/baseline=0.8864004, idea max abs hidden=1.0, confirmed=true" }, "how_to_run": "/home/maxwelhelp/main/bin/python3 stage2_bench.py", "files": [ "stage2_bench.py", "bench_report.json" ], "limitations": "Only the built-in dynamics track was tested; tabular, vision, and sequence tracks were not run. The matched baseline was a local unconstrained residual RNN rather than the bench GRU implementation, because the idea changes the recurrence and requires the same residual base architecture on both sides. The experiment used explicit Euler projection, one hidden width (64), one epoch budget (18), and three shared learning rates; implicit projected fixed-point updates, longer horizons, larger datasets, FLOPs, and external control benchmarks were not tested.", "bench_report": { "bench_version": 1, "track": "dynamics", "model": "rnn_small_matched_residual", "metric_direction": "lower is better", "n_seeds": 8, "baseline": { "sweep": [ { "cfg": { "lr": 0.001, "epochs": 18, "batch": 128 }, "mean": 0.009025773382745683 }, { "cfg": { "lr": 0.003, "epochs": 18, "batch": 128 }, "mean": 0.004750257066916674 }, { "cfg": { "lr": 0.006, "epochs": 18, "batch": 128 }, "mean": 0.0027194063586648554 } ], "best_cfg": { "lr": 0.006, "epochs": 18, "batch": 128 }, "full": { "mean": 0.0023904673871584237, "std": 0.0008984585761049981, "per_seed": [ 0.0016786052146926522, 0.00209295516833663, 0.002672365168109536, 0.004433699883520603, 0.001930432626977563, 0.002070770598948002, 0.0013639050303027034, 0.0028810054063796997 ], "n": 8 } }, "idea": { "config": { "lr": 0.006, "epochs": 18, "batch": 128 }, "mean": 0.00033889322003233247, "std": 0.00025331486786145277, "per_seed": [ 0.00025242450647056103, 0.0001881545758806169, 0.0002420831733616069, 0.0010012879502028227, 0.00028408446814864874, 0.0002892776974476874, 0.00017966072482522577, 0.0002741726639214903 ], "n": 8 }, "comparison": { "delta_mean": -0.002051574167126091, "idea_wins": 8, "n_pairs": 8, "per_seed_diffs": [ -0.0014261807082220912, -0.001904800592456013, -0.0024302819947479293, -0.0034324119333177805, -0.0016463481588289146, -0.0017814929015003145, -0.0011842443054774776, -0.0026068327424582094 ], "p_value": 0.0081, "mde": 0.0006128594980781139, "mde_rel_pct": 25.637643139178195, "verdict": "idea better (significant)", "system_worked": true }, "track_rationale": "Dynamics is the built-in structural match for stability/control and Lyapunov-style contraction.", "mechanism_signature": { "prediction": "projected dissipative dynamics reduces initial-state perturbation amplification and keeps hidden states in [-1,1]", "baseline_perturbation_ratio": 1.000967751024291, "idea_perturbation_ratio": 0.8872582511976361, "baseline_to_idea_ratio": 0.8864004362666207, "idea_max_abs_hidden": 1.0, "confirmed": true }, "idea_sweep": { "best_cfg": { "lr": 0.006, "epochs": 18, "batch": 128 }, "sweep": [ { "cfg": { "lr": 0.001, "epochs": 18, "batch": 128 }, "mean": 0.0020623414893634617 }, { "cfg": { "lr": 0.003, "epochs": 18, "batch": 128 }, "mean": 0.000677677511703223 }, { "cfg": { "lr": 0.006, "epochs": 18, "batch": 128 }, "mean": 0.0004209875514789019 } ] }, "parameterization": { "hidden": 64, "step": 0.12, "lambda": 0.1, "same_input_and_head": true, "lr_union_tested_on_both": [ 0.001, 0.003, 0.006 ] } }, "system_verdict": "worked", "practical_verdict": "helps", "mechanism_ok": 1, "system_judged": true }