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lab_reinforcement_learning/questions.md
Chris Proctor e752bb848b Refactor lab
2026-06-25 21:10:13 -04:00

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# Questions
## Checkpoint 1
1. How do you decide where to move in BabySnake? Explain how to choose moves
in enough detail that someone else could follow your instructions.
## Checkpoint 2
2. How many distinct states are there for BabySnake on a 4×4 grid? If we assume that all four
arrow keys are valid actions in every state, how many rows would the full Q-table contain?
3. The discount factor γ (gamma) can range from 0 to 1. What would be the effect of setting
γ to 0? What about 1?
4. The learning rate α (alpha) can also range from 0 to 1. What would be the effect of setting
α to 0? What about 1?
5. Calculate the new Q-value for ((2, 2, 3, 3), RIGHT). Explain your answer.
## Checkpoint 3
6. At what episode did the agent start reliably finding food?
7. Add `print(Q)` to `train_babysnake.py` before the `watch` call and run it again. Can you
read the policy? For a given state, does the highest Q-value point toward the food?
8. How does the trained agent's behavior compare to the reasoning you wrote down in question 1?