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BY571 / Soft-Actor-Critic-and-Extensions

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PyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.

reinforcement-learning parallel-computing pytorch multi-environment reinforcement-learning-algorithms continuous sac prioritized-experience-replay actor-critic-algorithm soft-actor-critic emphasizing-recent-experience munchausen-reinforcement-learning munchausen d2rl
  • Updated Feb 24, 2021
  • Python

BY571 / IQN-and-Extensions

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PyTorch Implementation of Implicit Quantile Networks (IQN) for Distributional Reinforcement Learning with additional extensions like PER, Noisy layer, N-step bootstrapping, Dueling architecture and parallel env support.

reinforcement-learning parallel-computing rainbow pytorch multi-environment dqn reinforcement-learning-algorithms parallel-processing iqn prioritized-experience-replay pytorch-implementation implicit-quantile-networks n-step-bootstrapping distributional-r noisy-layer munchausen
  • Updated Mar 4, 2023
  • Jupyter Notebook

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