Teach a Quadcopter How to Fly!
In this project, you will design an agent to fly a quadcopter, and then train it using a reinforcement learning algorithm of your choice!
- Clone the repository and navigate to the downloaded folder.
git clone https://github.com/udacity/RL-Quadcopter-2.git
cd RL-Quadcopter-2
- Create and activate a new environment.
conda create -n quadcop python=3.6 matplotlib numpy pandas keras sacred pymongo gym IPython
source activate quadcop
- Create an IPython kernel for the
quadcopenvironment.
python -m ipykernel install --user --name quadcop --display-name "quadcop"
- Open the notebook.
jupyter notebook Quadcopter_Project.ipynb
-
Before running code, change the kernel to match the
quadcopenvironment by using the drop-down menu (Kernel > Change kernel > quadcop). Then, follow the instructions in the notebook. -
You will likely need to install more pip packages to complete this project. Please curate the list of packages needed to run your project in the
requirements.txtfile in the repository.