Hands-On Reinforcement Learning for Games

Questions

Use these questions and exercises to reinforce the material you just learned. The exercises may be fun to attempt, so be sure to try atleast two to four questions/exercises:

Questions:

1. What are the names of the main components of an RL system? Hint, the first one is Environment.
2. Name the four elements of an RL system. Remember that one element is optional.
3. Name the three main threads that compose modern RL.
4. What makes a Markov state a Markov property?
5. What is a policy?

Exercises:

1. Using Chapter_1_2.py, alter the code so the agent pulls from a bandit with 1,000 arms. What code changes do you need to make?
2. Using Chapter_1_3.py, alter the code so that the agent pulls from the average value, not greedy/max. How did this affect the ...