PROJECT · Advanced
Perishable Inventory Replenishment
Train a reinforcement-learning agent to reorder a fast-spoiling grocery item each day -- batching against a flat per-delivery fee while avoiding both spoilage and stockouts -- and beat the store's daily base-stock rule.
Before you start
These courses cover the foundations you’ll use.
Already comfortable with these topics? Go straight to the project.
You’re ready when you can…
- Run seeded simulations and compare policies.
- Describe states, actions, rewards, and an episode.
- Keep policy tuning separate from final evaluation.
Prerequisites are recommendations, not requirements.