/Lunar-Lander-Reinforcement-Learning

Solving Lunar Lander with DQN Reinforcement Learning

Primary LanguageJupyter Notebook

Lunar-Lander-Reinforcement-Learning

This project has been implemented with the gymnasium Framework: https://gymnasium.farama.org/environments/atari/freeway/

Minimal Trained Final
Untrained Agent Final Agent

Setup Instructions

  1. Clone the Repository:

    git clone [https://github.com/JanMuehlnikel/Atari-Freeway-Reinforcement-Learning](https://github.com/JanMuehlnikel/Lunar-Lander-Reinforcement-Learning)
cd your-repo

  2. Create and Activate a New Conda Environment:

    conda create --name LunarEnv python=3.10
conda activate LunarEnv

  3. Install pip in the New Conda Environment:

    conda install pip

  4. Install Packages from requirements.txt:

    pip install -r requirements.txt