Practice — Model-Based RL & Planning (5 questions)

You advise two teams in the same quarter:

• Team Chess: building an agent to play a board game with fully known rules, deployed against a fast internal simulator that can run millions of games per day on existing infrastructure.
• Team Notify: building an agent to decide which of several push notifications to send a user next, to maximize 30-day retention, using only logged historical interaction data plus live traffic.

1. For each team, recommend a model-based or model-free approach (or a specific blend) and justify it using the accuracy of the model each team could realistically build.
2. Team Notify's lead proposes: "let's learn a world model of user behavior and use MCTS to plan a multi-step sequence of notifications that maximizes 30-day retention." Explain concretely what would go wrong with this proposal.
3. What would you recommend Team Notify build instead, and why does it avoid the failure mode you identified in part 2?