# Evidence: Policy gradients and PPO

Copy this template into your own portfolio and fill it after running your modified exercise.

## Evidence required

Keep the exact small-state policy-gradient comparison, actual training curves and frozen PPO reference quantities. Diagnose changed clipping signs and distinguish Monte Carlo variation from an incorrect objective.

- Command: `python3 phases/12-rl/03-policy-gradients-and-ppo/code/main.py`
- Working directory: repository root
- Python / JAX / NumPy versions: 
- Hardware and device: 
- My prediction before running: 
- My change to the exercise: 
- Exit code and meaningful output: 
- Why the result supports or contradicts my prediction: 
- Checkpoint result: 
- Artifact link or saved filename: 
- Portfolio status: saved in local workspace