RBDoom is a Rainbow-DQN based agent for playing the first-person shooter game Doom

Applying the DQN-Agent from keras-rl to Starcraft 2 Learning Environment and modding it to to use the Rainbow-DQN algorithms.

Graph-based Deep Q Network for Web Navigation

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.

Tensorflow - Keras /PyTorch Implementation ⚡️ of State-of-the-art DeepQN for RL Gym benchmarks 👨‍💻

Implementation and evaluation of the RL algorithm Rainbow to learn to play Atari games.

🐳 Implementation of various Distributional Reinforcement Learning Algorithms using TensorFlow2.

Reinforcement Learning on Atari

The implement of all kinds of dqn reinforcement learning with Pytorch

🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

Example Rainbow DQN implementation with ReLAx

Playing 2048 with Rainbow agent

ReLAx - Reinforcement Learning Applications Library

Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.

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.

An implementation of an Autonomous Vehicle Agent in CARLA simulator, using TF-Agents

A library for ready-made reinforcement learning agents and reusable components for neat prototyping

Build and test DRL algorithms in different environments