Chapter 1

Reinforcement Learning Engineering

Close the workbook by making RL results measurable, reproducible, and comparable across seeds, environments, checkpoints, and evaluation protocols.

• 1. Experiment Tracking→
• 2. Seeds and Reproducibility→
• 3. Evaluation Protocols→
• 4. Comparing Runs Fairly→
• 5. Environment and Reward Contracts→
• 6. Distributed RL and Deployment→
• 7. RL Engineering Checklist→