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
Reinforcement learning algorithm implementation
Categorical DQN from 'A distributional Perspective on Reinforcement Learning'
Implementation and evaluation of the RL algorithm Rainbow to learn to play Atari games.
ReLAx - Reinforcement Learning Applications Library
Example Categorical DQN implementation with ReLAx
Yet another deep reinforcement learning
Example Rainbow DQN implementation with ReLAx
Tensorflow - Keras /PyTorch Implementation ⚡️ of State-of-the-art DeepQN for RL Gym benchmarks 👨💻
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