feat(PPO_Bot): reward + trajectory + GAE + PPO training (#16)
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>
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{ pkgs ? import <nixpkgs> {} }:
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pkgs.mkShell {
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buildInputs = with pkgs; [
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openblas
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];
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}
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