jgrusewski e9e4bd54ac plan: Adaptive Training Dynamics Layers 1+2 implementation plan ...

Task 1: Reward rank normalization kernel (SNR amplification)
Task 2: Q-gap momentum for spread gradient (plateau modulation)
Task 3: H100 integration test (50 epochs, compare to train-w6qfd)

Layers 3+4 (dir→mag conditioning, variance sizing) deferred to
separate plan after L1+L2 validation.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-14 21:42:57 +02:00

..

infra

feat(infra): GPU training launcher with local/cloud routing

2026-02-23 11:19:58 +01:00

plans

feat(dqn): enable Branching DQN with 45 factored actions (5×3×3)

2026-03-11 22:00:13 +01:00

superpowers

plan: Adaptive Training Dynamics Layers 1+2 implementation plan

2026-04-14 21:42:57 +02:00