You can run this code on your own machine or on Google Colab (Colab is not completely supported).

1. Local option: If you choose to run locally, you will need to install MuJoCo and some Python packages; see installation.md from homework 1 for instructions. There are two new package requirements (opencv-python and gym[atari]) beyond what was used in the previous assignments; make sure to install these with pip install -r requirements.txt if you are running the assignment locally.

2. Docker: You can also run this code in side of a docker image. You will need to build the docker image using the provided docker file

3. Colab: The first few sections of the notebook will install all required dependencies. You can try out the Colab option by clicking the badges below:

If not done yet, install anaconda by following the instructions here. Then create a anaconda environment, activate it and install the requirements in requirements.txt.

conda create -n roble python=3.8
conda activate roble
pip install -r requirements.txt

If having issues with Pytorch and GPU, make sure to install the compatible version of Pytorch for your CUDA version here

python run_hw1_bc.py alg.n_iter=1 alg.do_dagger=false

python run_hw6_sim2real.py alg.n_iter=1

Assignments for UdeM roble: Robot Learning Course. Based on Berkeley CS 285: Deep Reinforcement Learning, Decision Making, and Control.