Lecture
Reinforcement Learning Basics
Description
This lecture covers the fundamentals of reinforcement learning, focusing on topics such as Q-learning, epsilon-greedy policies, and Monte Carlo estimation. It explains how agents interact with environments, learn optimal policies, and balance exploration and exploitation.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.