LMU_RFL_SoSe24

Thema 5: RL-Policy-Training unter Vermeidung von Zuständen mit sehr geringer Datendichte

🛠️ Setup

Install PyENV:
Follow the instructions on the PyENV GitHub page to install PyENV.
Set Up Python 3.10.6:
Ensure PyEnv has Python 3.10.6 installed (or any version > 3.8.0). Run the following commands:
```
pyenv update
pyenv install 3.10.6
```
Clone the Repository:
Clone this repository to your local machine:
```
git clone https://github.com/LeonLantz/LMU_RFL_SoSe24
```
Set Python Version:
Create an instance of Python 3.10.6 for your project. This will generate a .python-version file:
```
pyenv local 3.10.6
```
Determine Python Path:
Find the path to your Python 3.10.6 executable:
```
pyenv which python
```
Example output: C:\Users\<USER>\.pyenv\pyenv-win\versions\3.10.6\python.exe
Create Virtual Environment:
Create a virtual environment using the specified Python version:
```
C:\Users\<USER>\.pyenv\pyenv-win\versions\3.10.6\python.exe -m venv .venv
```
Activate the Virtual Environment:
Activate your virtual environment:
- On Windows:
```
.venv\scripts\activate
```
- On Linux/Mac:
```
source .venv/bin/activate
```
Install Required Packages:
Install all necessary packages from requirements.txt into your virtual environment:
```
pip install -r requirements.txt
```
Your are done!
Open the project in your preferred IDE (e.g., VS Code or JupyterLab) and start working!