Run exactly one experiment trial end-to-end.
Steps:
- •Confirm environment installation steps exist (env/ + README).
- •Choose a canonical command (e.g., python -m scripts.train --config configs/paper.yaml --seed 0).
- •Run the command and capture:
- •stdout/stderr
- •results/<run_id>/config.json
- •results/<run_id>/metrics.*
- •results/<run_id>/summary.json
- •Validate basic sanity checks:
- •learning curve is not all NaN
- •episodic return is in plausible bounds
- •eval runs produce outputs
- •Update README with the one-liner command and expected runtime.