SirStone eadd177d3b 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>

2026-08-16 15:27:15 +02:00

..

test_network.nim

feat(PPO_Bot): network forward pass + action mapping (#14)

2026-08-16 15:10:46 +02:00

test_state.nim

feat(PPO_Bot): enemy tracker + 42-float state vector (#15)

2026-08-16 15:12:13 +02:00

test_training.nim

feat(PPO_Bot): reward + trajectory + GAE + PPO training (#16)

2026-08-16 15:27:15 +02:00