Corpus ID: 235755271

RRL: Resnet as representation for Reinforcement Learning

@article{Shah2021RRLRA,
  title={RRL: Resnet as representation for Reinforcement Learning},
  author={Rutav Shah and Vikash Kumar},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.03380}
}
  • Rutav Shah, Vikash Kumar
  • Published 2021
  • Computer Science
  • ArXiv
The ability to autonomously learn behaviors via direct interactions in uninstrumented environments can lead to generalist robots capable of enhancing productivity or providing care in unstructured settings like homes. Such uninstrumented settings warrant operations only using the robot’s proprioceptive sensor such as onboard cameras, joint encoders, etc which can be challenging for policy learning owing to the high dimensionality and partial observability issues. We propose RRL: Resnet as… Expand
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  • ArXiv
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