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model_pong.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:96883ed257d0d3f18b836e7b7592bbb3cb72e802de400a89da98733667c88c90
+oid sha256:d6c8b9235347bea94e7e5f5f0f225d4c1dbd13a749d5e28920c75c91902ecb11
 size 2435368

predict.py

@@ -1,4 +1,4 @@
-"""Optimized blend: Pong AR weight 0.85->0.65, Sonic unchanged 0.7->0.3."""
+"""Non-linear Sonic blend: steps 0-1 AR=0.8, steps 2-4 AR=0.5, steps 5-7 AR=0.2."""
 import sys
 import os
 import numpy as np
@@ -225,9 +225,10 @@ def predict_next_frame(ens, context_frames: np.ndarray) -> np.ndarray:
 
             ar_pred = torch.stack(ar_preds, dim=1)
 
+            ar_weights = [0.8, 0.8, 0.5, 0.5, 0.5, 0.2, 0.2, 0.2]
             predicted = torch.zeros_like(direct_pred)
             for step in range(PRED_FRAMES):
-                ar_weight = 0.7 - (step / (PRED_FRAMES - 1)) * 0.4
+                ar_weight = ar_weights[step]
                 direct_weight = 1.0 - ar_weight
                 predicted[:, step] = ar_weight * ar_pred[:, step] + direct_weight * direct_pred[:, step]