This repository contains the materials necessary for the ending Hackathon for the 2020 RL@XHEC course.

The goal is for the students to define the rewards and train&tweak the agent to achieve the best score possible.

How-to use it:

1. Clone this repository : git clone https://gitlab.com/the_insighters/x-hec/hackathon-rlxhec.git
2. Enter the repo folder cd hackathon-rlxhec
3. (Optional if already done) : install poetry curl -sSL https://raw.githubusercontent.com/python-poetry/poetry/master/get-poetry.py | python -
4. Install the libraries : poetry install
5. You can now run main.py using poetry: poetry run python main.py
6. Modify main.py to tweak the agent and reward.
7. Good luck !

To-do list

• Transform the Rocker lander from https://github.com/EmbersArc/gym_rocketLander/blob/master/gym/envs/box2d/rocket_lander.py into an exploitable environment.
• Customize the environment for the reward function to be definable from main.py
• Create a nice training&testing interface
• Add a save Agent functionnality
• Solve the task with PPO)
• Add video recording (instead of just being able to watch the episode at the time it is done)
• Add a cue when the task is "solved"
• Add landed and landed full to available variables
• Add difficulty levels (done but not very useful, maybe a score system will be beter)
• Add score
• Add variables description
• Tweak the difficulty for a nice experience
• Test the exercise with different people to measure difficulty and time to beat

Architecture:

• main.py : This is where the student will define reward function and agent and will be able to train and see the results
• utils.py : Scripts to help the students. non directly related to RL.
• gym_rocketLander (submodule) : Custom gym environment for SpaceX Rocket Lander (original work from EmbersArc modified to tweak difficulty)
• requirements.txt : Specifies the needed libraries
• .gitignore : Specifies which files to ignore when commiting.
• data (folder): stores the data needed for the plots and agent. It is of no use for the user
• figs (folder): stores the graphs (rewards over the episodes)
• vids (folder): stores the vids of the agent's execution for each batch

Variable explanation

Disclaimer: The environment is based on https://github.com/EmbersArc/gym_rocketLander