This repository contains all the assignments I've completed as part of my Reinforcement Learning course at the University of Tehran. Each assignment is stored in a separate folder, named according to the assignment number. Each folder contains the assignment instructions, report, and the code I've written to complete the assignment.
The assignments cover a range of topics, including:
- Markov decision processes
- Q-learning
- Deep reinforcement learning
- Policy gradient methods
Each assignment builds on the concepts covered in the previous assignments, so I recommend reviewing them in order.
To use this repository, simply clone or download the repository to your local machine. You can then navigate to the relevant assignment folder and review the instructions, report, and code.
In each assignment folder, you'll find a README.md file that provides a brief overview of the assignment and instructions on how to run the code.
The assignments in this repository were completed using a variety of technologies, including:
- Python
- NumPy
- Pytorch
- OpenAI Gym
This repository is my personal collection of assignments, so I'm not currently accepting contributions. However, I'm always happy to receive feedback and suggestions for improvement. If you have any comments or suggestions, feel free to contact me.