Эксперимент: Certainty-Equivalent Auxiliary Critic (#1421)

{ "worked": false, "confidence": 8, "verdict": "Built a bounded stochastic-control toy experiment with stable log-mean-exp, a direct sampled critic baseline, and a joint value plus auxiliary certainty-equivalent critic. The math check passed and showed sample CE error decreasing from 0.716 at K=2 to 0.113 at K=128. However, the auxiliary CE RMSE was 9.59 versus the baseline value-target RMSE of 6.89, and it was slower; its lower Bellman residual was not enough to establish the claimed reliable CE approximation or stability win.", "metrics": { "baseline": "Direct critic across 3 seeds: Bellman RMSE 6.88±0.06, value-target RMSE 6.885±0.043, runtime 7.08±0.25 s.", "idea": "Auxiliary critic across 3 seeds: Bellman RMSE 2.66±0.28, value-target RMSE 6.193±0.072, CE RMSE 9.59±0.30, runtime 9.58±0.10 s." }, "how_to_run": "/home/maxwelhelp/main/bin/python3 experiment.py", "files": [ "experiment.py", "results.json" ], "limitations": "This was a small one-step stochastic critic test rather than SAC or a multi-step environment. Actor learning, risk-sensitive return, action-gradient variance, and FLOP-normalized comparisons were not tested. The high-K reference used the learned target critic rather than an analytic ground-truth value, and the toy training setup remained imperfectly calibrated." }