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Implementation of the DRDQN algrotihm described in our CIKM'21 paper titled "Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays"

baranwa2/DelayResolvedRL

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DelayResolvedRL

Implementation of the DRDQN algrotihm described in our CIKM'21 paper titled "Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays"

System requirements

  • Python 3.6.9
  • Tensorflow 2.1
  • OpenAI Gym 0.18.0
The repository includes experiemnts on standard Gym enviroments (and W-maze) with both constant and stochastic delays.

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Implementation of the DRDQN algrotihm described in our CIKM'21 paper titled "Revisiting State Augmentation methods for Reinforcement Learning with Stochastic Delays"

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