Note: This repo will be updated as I implement different types of RL models. Blog can be found here: https://vulcan-332.github.io/reinforcement-learning/2025/12/07/rl-models.html

The purpose of this post is to implement different RL algorithms in code, going beyond theory. The examples will focus on simple environments to make it easier to understand the inner workings of the algorithms. For speeding up the setup, environments are pre-built and imported from Gymnasium.

You can use any package manager, I will be using conda. Basic packages are numpy, matplotlib, and gymnasium.

conda create -n deep_rl python=3.10
conda activate deep_rl
pip install gymnasium
pip install matplotlib