UPDATE: VBAF v4.0.0 is complete!

I completed a 27-phase DQN implementation in pure PowerShell 5.1.

No Python. No PyTorch. No GPU.

14 enterprise agents trained on real Windows data.

Best improvement: +117.5% over random baseline.

Phase 27 AutoPilot orchestrates all 13 pillars simultaneously.

Lessons learned the hard way:

– Symmetric distance rewards prevent action collapse

– Dead state signals (OffHours=0 all day) kill learning

– Distribution shaping beats reward shaping for 4-action agents

github.com/JupyterPS/VBAF