Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
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Updated
Mar 29, 2023 - Python
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
A library for ready-made reinforcement learning agents and reusable components for neat prototyping
The implement of all kinds of dqn reinforcement learning with Pytorch
🐳 Implementation of various Distributional Reinforcement Learning Algorithms using TensorFlow2.
Graph-based Deep Q Network for Web Navigation
An implementation of an Autonomous Vehicle Agent in CARLA simulator, using TF-Agents
ReLAx - Reinforcement Learning Applications Library
Applying the DQN-Agent from keras-rl to Starcraft 2 Learning Environment and modding it to to use the Rainbow-DQN algorithms.
RBDoom is a Rainbow-DQN based agent for playing the first-person shooter game Doom
Implementation and evaluation of the RL algorithm Rainbow to learn to play Atari games.
Comparison of different Deep Reinforcement Learning (DRL) Frameworks. This repository includes "tf-agents", "RLlib" and will soon support "acme" as well.
Minimum viable reinforcement learning algorithms for your educational convenience.
Tensorflow - Keras /PyTorch Implementation ⚡️ of State-of-the-art DeepQN for RL Gym benchmarks 👨💻
Reinforcement learning project for Atari Breakout
We use the Rainbow DQN model to build agents that play Ms-Pacman, Atlantis and Demon Attack. We make modifications to the model that allow much faster convergence on Ms-Pacman with respect to Deepmind's original paper and obtain comparable performance.
Playing 2048 with Rainbow agent
Build and test DRL algorithms in different environments
Reinforcement Learning on Atari
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