Welcome to the Reinforcement Learning Tutorial, which is part of the lecture series "Computational Modeling"!
This project relies on Conda, an open source package and environment management system for Windows, Linux, and macOS. Conda allows you to install multiple versions of software packages and switching easily between them.
Please install Conda on the machine you intend to use for the lab.
There are two versions of Conda available, namely Miniconda and Anaconda. Anaconda provides additional functionalities, such as a GUI. However, Miniconda is absolutely sufficient for this tutorial.
- Create the environment using the provided YAML file:
conda env create -f environment.yml
- Activate the Conda environment:
conda activate RL-Tutorial
- Start training on your custom environment
python main.py
Note: This codebase is designed for active learning. It will not run successfully out of the box!
The code has several open ToDos and is intended to be completed during the lecture. The fully functioning environment will be provided via the usual channels after the lecture.