Python Reinforcement Learning
上QQ阅读APP看书,第一时间看更新

Questions

The question list is as follows:

  1. What is the Markov property?
  2. Why do we need the Markov Decision Process?
  3. When do we prefer immediate rewards?
  4. What is the use of the discount factor?
  5. Why do we use the Bellman function?
  6. How would you derive the Bellman equation for a Q function?
  7. How are the value function and Q function related?
  8. What is the difference between value iteration and policy iteration?