An implementation of the laserhockey environment agents by:
DQN: Agniv Sharma
SAC: Batuhan Ozcomlekci
DDPG: Dhruv Behl
Create a new environment_<method>.yaml
file using anaconda like:
conda env create -f environment_sac.yml
Then execute the code below:
python3 -m pip install git+https://github.com/martius-lab/laser-hockey-env.git
or add the following line to your Pipfile
laserhockey = {editable = true, git = "https://git@github.com/martius-lab/laser-hockey-env.git"}
Checkpoint files can be found in the drive https://drive.google.com/drive/folders/1zDMBWRs9vSFvKmyMMCFNzA-KhtNL4zVh?usp=drive_link
laserhockey.hockey_env.HockeyEnv
A two-player (one per team) hockey environment. For our Reinforcement Learning Lecture @ Uni-Tuebingen. See Hockey-Env.ipynb notebook on how to run the environment.
The environment can be generated directly as an object or via the gym registry:
env = gym.envs.make("Hockey-v0")
There is also a version against the basic opponent (with options)
env = gym.envs.make("Hockey-One-v0", mode=0, weak_opponent=True)
A laser-hockey game implementation within openAI gym using the Box2D engine. It is quite a challenging environment See Laser-Hockey-Env.ipynb notebook on how to run the environment.