# Additional Readings [[additional-readings]]

These are **optional readings** if you want to go deeper.

## Monte Carlo and TD Learning [[mc-td]]

To dive deeper into Monte Carlo and Temporal Difference Learning:

- <a href="https://stats.stackexchange.com/questions/355820/why-do-temporal-difference-td-methods-have-lower-variance-than-monte-carlo-met">Why do temporal difference (TD) methods have lower variance than Monte Carlo methods?</a>
- <a href="https://stats.stackexchange.com/questions/336974/when-are-monte-carlo-methods-preferred-over-temporal-difference-ones"> When are Monte Carlo methods preferred over temporal difference ones?</a>

## Q-Learning [[q-learning]]

- <a href="http://incompleteideas.net/book/RLbook2020.pdf">Reinforcement Learning: An Introduction, Richard Sutton and Andrew G. Barto Chapter 5, 6 and 7</a>
- <a href="https://youtu.be/Psrhxy88zww">Foundations of Deep RL Series, L2 Deep Q-Learning by Pieter Abbeel</a>
