There are 2 repositories under dqn-pytorch topic.
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
A PyTorch library for building deep reinforcement learning agents.
DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN
A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".
Deep Q-Learning (DQN) implementation for Atari pong.
Important Note fastrl version 2 is being developed at fastrl. Note the link in the readme
SUMO Pytorch Deep Reinforcement Learning Traffic Signal Control
PyTorch implementation of the state-of-the-art distributional reinforcement learning algorithm Fully Parameterized Quantile Function (FQF) and Extensions: N-step Bootstrapping, PER, Noisy Layer, Dueling Networks, and parallelization.
PyTorch agents and tools for (Deep) Reinforcement Learning
Reinforcement Learning - Implementation of Exercises, algorithms from the book Sutton Barto and David silver's RL course in Python, OpenAI Gym.
This code is the result of the collaboration of RL Turkey team.
Solving Atari Pong Game w/ Duel Double DQN in Pytorch
Reinforcement Learning for Optimal inventory policy
Integrate AutoRL into DQN to implement a single traffic signal control system.
Grid-scale li-ion battery optimisation for wholesale market arbitrage, using pytorch implementation of dqn, double dueling dqn and a noisy network dqn.
PyTorch implementation of RIC for conveyor systems with Deep Q-Networks (DQN) and Profit-Sharing (PS). Wang, T., Cheng, J., Yang, Y., Esposito, C., Snoussi, H., & Tao, F. (2020). Adaptive Optimization Method in Digital Twin Conveyor Systems via Range-Inspection Control. IEEE Transactions on Automation Science and Engineering.
Deep Q learning algorithm written on PyTorch for solving 2D robot arm reacher
Reinforcement Learning Tutorials & other bedtime stories in PyTorch
Reinforcement learning modular with pytorch
Control Traffic lights intelligently with Reinforcement Learning!
This project is a pipeline that connects a Matlab simulation (Simulink) to an OpenAI Gym wrapper for PyTorch Reinforcement Learning using the DQN algorithm.
Minimum viable reinforcement learning algorithms for your educational convenience.
Use the movements of your thumb to play Pong against a pre-trained Double-DQN-Agent. I used Google-Colab for training the pyTorch model and created the Pong environment with Pygame.
My solution to the Harvest Competition
Studying emergent communication among agents in cooperative and competitive environments using Reinforcement Learning, game theory and replicator dynamics
Experimenting with PyTorch DQNs on various environments