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chore(*): Update todos
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@@ -12,7 +12,6 @@ The training pipeline is built — see `TRAINING.md` (self-play PPO via the vend
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- [ ] Frozen-opponent league: train the live policy against a *pool* of past exported checkpoints, sampled per-episode (today's `--opponent-mode=frozen` only supports one fixed model per run) to prevent self-play strategy collapse on long runs.
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- [ ] Richer state setter / curriculum: aerial states, wall plays, rebound scenarios as skill grows (beyond the score/defend/draw staging already in place).
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- [ ] Main-menu difficulty picker (Match already takes `bot_model_path`/`bot_reaction_ticks`/`bot_action_noise` exports).
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- [ ] Optional: exported headless Linux build for faster parallel training instances (train.py currently runs the project from source, which is fine but re-parses scripts per instance).
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## Multiplayer (long term)
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