Save ACAdamStates (m/v tensors + t counters) as .npy files alongside
network weights in latest/ and checkpoint dirs; save round counter to
round_counter.txt. loadBestAvailable restores both on startup; fresh
start works unchanged when files are absent.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- enemy_tracker: toggle lastOvershootDir each tick; make getRadarTurnRate take var tracker
- training: remove threadvar Adam globals; pass adamStates as var param to ppoUpdate; export ACAdamStates
- PPO_Bot: carry ACAdamStates through TrainingArgs/TrainingResult; drop trainingDone bool and Lock — use resultChan.tryRecv() directly as synchronisation
- weights: sort checkpoint dirs newest-first by mtime instead of hardcoded order
- tests/test_training: pass explicit ACAdamStates to ppoUpdate
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Manual-backprop PPO with Adam: TrajectoryBuffer, computeGAE, ppoUpdate
(4 epochs, minibatch 64, clip 0.2, grad norm 0.5). Reward helpers
computeTickReward/computeRoundReward. Bot wired: tick transitions
collected in run loop, ppoUpdate called on onRoundEnded. Fix: add
arraymancer import to PPO_Bot.nim so Tensor resolves at top level.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>