Record first-open replay result
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@@ -246,6 +246,32 @@ Primary comparison is the `eps=0.05` confirmation run and the pure external
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sampling run. Success requires bad-open rate and score/opened color to improve
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sampling run. Success requires bad-open rate and score/opened color to improve
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together without a large score-diff regression.
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together without a large score-diff regression.
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Result:
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- Run: `runs/2026-05-09_235808_first-open-reweight-50-512x3-det-500-indexed`
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- W&B group: `first-open-replay-v1`
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- Commit: `8217cec` (`Speed up first-open memory sampling`)
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The scan-based first implementation was stopped after 12 iterations because
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first-open sampling scanned the full replay memory and pushed iteration time
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above 60 seconds. The indexed-memory version kept first-open sampling near
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0.25 seconds per player at 4M advantage samples and completed 500 iterations.
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Final `safe_heuristic_strict` comparison:
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| Run | Iter | Score diff | Win rate | Bad open | Score/opened |
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| --- | ---: | ---: | ---: | ---: | ---: |
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| baseline `confirm-eps-005-zero-512x3-det-500` | 500 | -61.24 | 0.06 | 0.903 | -8.30 |
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| pure external `pure-external-512x3-det-500` | 500 | -50.38 | 0.06 | 0.925 | -9.79 |
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| first-open reweight 50% indexed | 500 | -52.20 | 0.07 | 0.919 | -9.39 |
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Conclusion: first-open replay reweighting alone did not solve selectivity. It
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improved score diff versus the baseline final checkpoint, but it did not reduce
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bad-open rate and made score/opened color worse. The run briefly looked better
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around 120-200 iterations, then regressed by 300-500 iterations. This suggests
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the replay emphasis is not enough if the underlying target does not separate
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good first opens from bad first opens.
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### 3. Short open-selectivity ablation
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### 3. Short open-selectivity ablation
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Run a 200-300 iteration ablation only after the target audit identifies a
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Run a 200-300 iteration ablation only after the target audit identifies a
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