This implementation is based on Deep Inverse Q-learning with Constraints

Arxiv : https://arxiv.org/abs/2008.01712

Blog Post: http://nrprojects.cs.uni-freiburg.de/foundations.html#inverse

Using the Inverse Q-Learning on vector states Evaluation on the LunarLander enviroment from open ai gym The expert samples are generated for an policy that solved the problem with an reward at least 200

1. Clone the repository and navigate to the downloaded folder.

     git clone https://github.com/ChrisProgramming2018/IQL_Lunar_Lander.git
     cd IQL_Lunar_Lander 

2. Create a conda enviroment

     conda create -n iql python=3.7

3. Activate the Enviroment

	conda activate iql

4. Install all dependencies, use the requirements.txt file

	pip3 install -r requirements.txt