Corpus ID: 59606283

Distilling Policy Distillation

@article{Czarnecki2019DistillingPD,
  title={Distilling Policy Distillation},
  author={W. Czarnecki and Razvan Pascanu and Simon Osindero and Siddhant M. Jayakumar and G. Swirszcz and Max Jaderberg},
  journal={ArXiv},
  year={2019},
  volume={abs/1902.02186}
}
  • W. Czarnecki, Razvan Pascanu, +3 authors Max Jaderberg
  • Published 2019
  • Computer Science, Mathematics
  • ArXiv
  • The transfer of knowledge from one policy to another is an important tool in Deep Reinforcement Learning. This process, referred to as distillation, has been used to great success, for example, by enhancing the optimisation of agents, leading to stronger performance faster, on harder domains [26, 32, 5, 8]. Despite the widespread use and conceptual simplicity of distillation, many different formulations are used in practice, and the subtle variations between them can often drastically change… CONTINUE READING
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