Modularized Implementation of Deep RL Algorithms in PyTorch
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Updated
Apr 16, 2024 - Python
Modularized Implementation of Deep RL Algorithms in PyTorch
Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch
Clean, Robust, and Unified PyTorch implementation of popular DRL Algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)
The implement of all kinds of dqn reinforcement learning with Pytorch
ReLAx - Reinforcement Learning Applications Library
Reinforcement learning algorithm implementation
Implementation and evaluation of the RL algorithm Rainbow to learn to play Atari games.
Categorical DQN from 'A distributional Perspective on Reinforcement Learning'
Tensorflow - Keras /PyTorch Implementation ⚡️ of State-of-the-art DeepQN for RL Gym benchmarks 👨💻
Yet another deep reinforcement learning
Example Rainbow DQN implementation with ReLAx
Example Categorical DQN implementation with ReLAx
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