Corpus ID: 199452974

DoorGym: A Scalable Door Opening Environment And Baseline Agent

@article{Urakami2019DoorGymAS,
  title={DoorGym: A Scalable Door Opening Environment And Baseline Agent},
  author={Yusuke Urakami and Alec Hodgkinson and Casey Carlin and Randall Leu and Luca Rigazio and P. Abbeel},
  journal={ArXiv},
  year={2019},
  volume={abs/1908.01887}
}
  • Yusuke Urakami, Alec Hodgkinson, +3 authors P. Abbeel
  • Published 2019
  • Computer Science, Engineering
  • ArXiv
  • Reinforcement Learning (RL) has brought forth ideas of autonomous robots that can navigate real-world environments with ease, aiding humans in a variety of tasks. RL agents have just begun to make their way out of simulation into the real world. Once in the real world, benchmark tasks often fail to transfer into useful skills. We introduce DoorGym, a simulation environment intended to be the first step to move RL from toy environments towards useful atomic skills that can be composed and… CONTINUE READING
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