Welcome to the Reinforcement Learning Assignments repository! This repository contains assignments related to Reinforcement Learning (RL). These assignments are designed to provide students a deeper understanding of RL algorithms Implementation.
Reinforcement Learning is a branch of machine learning that focuses on training agents to make sequential decisions in an environment to maximize a cumulative reward. This repository contains assignments that provide a pure mathematical understanding of RL algorithms by implementing them from scratch, without relying on any built-in libraries. By working on these assignments, students will gain valuable insights into the inner workings of RL algorithms.
- Install Python by downloading it from the official Python website and following the installation instructions.
- Install numpy
pip install numpyTo use the assignments, simply clone or download the repository to your local machine. No additional installation steps are required, as the code is implemented using basic Python functionality.
Contributions to this repository are welcome! If you have any improvements or additional RL assignments to share, please feel free to submit a pull request. Make sure to adhere to the existing coding style and provide a clear description of the changes made.
The code in this repository follows the guidelines and methodologies outlined in 'Reinforcement Learning: An Introduction' (2nd edition) by Sutton and Barto.