Maze¶
A collection of environments in which an agent has to navigate through a maze to reach certain goal position. Two different agents can be used: a 2-DoF force-controlled ball, or the classic Ant
agent from the Gymnasium MuJoCo environments. The environment can be initialized with a variety of maze shapes with increasing levels of difficulty.
Reference¶
These environments were first introduced in “D4RL: Datasets for Deep Data-Driven Reinforcement Learning” by Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine. Which can be cited as follows:
@misc{fu2020d4rl,
title={D4RL: Datasets for Deep Data-Driven Reinforcement Learning},
author={Justin Fu and Aviral Kumar and Ofir Nachum and George Tucker and Sergey Levine},
year={2020},
eprint={2004.07219},
archivePrefix={arXiv},
primaryClass={cs.LG}
}