Highlights
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Soft-Actor-Critic-and-Extensions
Soft-Actor-Critic-and-Extensions PublicPyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.
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Upside-Down-Reinforcement-Learning
Upside-Down-Reinforcement-Learning PublicUpside-Down Reinforcement Learning (⅂ꓤ) implementation in PyTorch. Based on the paper published by Jürgen Schmidhuber.
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DQN-Atari-Agents
DQN-Atari-Agents PublicDQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN
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IQN-and-Extensions
IQN-and-Extensions PublicPyTorch Implementation of Implicit Quantile Networks (IQN) for Distributional Reinforcement Learning with additional extensions like PER, Noisy layer, N-step bootstrapping, Dueling architecture and…
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Deep-Reinforcement-Learning-Algorithm-Collection
Deep-Reinforcement-Learning-Algorithm-Collection PublicCollection of Deep Reinforcement Learning Algorithms implemented in PyTorch.
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