Corpus ID: 225072922

How to Make Deep RL Work in Practice

@article{Rao2020HowTM,
  title={How to Make Deep RL Work in Practice},
  author={Nirnai Rao and Elie Aljalbout and Axel Sauer and Sami Haddadin},
  journal={ArXiv},
  year={2020},
  volume={abs/2010.13083}
}
In recent years, challenging control problems became solvable with deep reinforcement learning (RL). To be able to use RL for large-scale real-world applications, a certain degree of reliability in their performance is necessary. Reported results of state-of-the-art algorithms are often difficult to reproduce. One reason for this is that certain implementation details influence the performance significantly. Commonly, these details are not highlighted as important techniques to achieve state-of… Expand
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