Basic implementation of gridworld game for reinforcement learning research. This environment is used in the following paper:
How You Act Tells a Lot: Privacy-Leakage Attack on Deep Reinforcement Learning
Consider cite the paper:
@inproceedings{pan2019you,
author = {Xinlei Pan and
Weiyao Wang and
Xiaoshuai Zhang and
Bo Li and
Jinfeng Yi and
Dawn Song},
title = {How You Act Tells a Lot: Privacy-Leaking Attack on Deep Reinforcement
Learning},
booktitle = {Proceedings of the 18th International Conference on Autonomous Agents
and MultiAgent Systems, {AAMAS}},
pages = {368--376},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
year = {2019},
}
install virtual environment for gridworld
cd gym-gridworld
conda env create -f environment.yml
conda activate gridworld
pip install -e .
import gym
import gym_gridworld
env = gym.make('gridworld-v0')
_ = env.reset()
_ = env.step(env.action_space.sample())
In order to visualize the gridworld, you need to set env.verbose
to True
env.verbose = True
_ = env.reset()