Intro to Q-learning in RL

Resource | v1 | created by janarez |
Type Interactive
Created 2021-04-30
Identifier unavailable


In this tutorial, we aim to provide readers with a high-level overview of the fundamentals of RL as well as example code in Python, introducing the OpenAI Gym library. We begin with building intuitions about what is considered an RL problem and we introduce formal definitions as well as key terminologies that are used to describe and model an RL application. In parallel, we will focus on solving a concrete example of an RL problem (CartPole) using a classic RL algorithm called Q-learning.


about Q-learning

Q-learning is a model-free reinforcement learning algorithm to learn the value of an action in a part...

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Clearly explained with a simple example. Jupyter notebook, so you can run the experiment yourself in the browser.