Chapter 5
- In Q-learning, what does the Q stand for (you will have to research this on the internet)?
The origin of Q-learning is the doctoral thesis of Christopher John Cornish Hellaby Watkins from King’s College, London, May, 1989 (https://www.researchgate.net/publication/33784417_Learning_From_Delayed_Rewards). Evidently, the Q just stands for Quantity.
- What could we do to limit the number of states that the Q-learning algorithm must search through?
Only pick the Q-states that are relevant and are follow-ons to the current state. If one of the states is impossible to reach from the current position, or state, then don’t consider it.
- What effect does changing the learning rate have on the learning process?
If the learning rate is too small, the training can take a very long time. If the learning rate is too large, the system does not learn a path but instead overshoots and may miss the minimum or optimum solution. If the learning rate is too big, the solution...
