There are 3 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.
PyTorch implementations of algorithms from "Reinforcement Learning: An Introduction by Sutton and Barto", along with various RL research papers.
DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN
Deep Q-Learning (DQN) implementation for Atari pong.
A PyTorch Implementation of "Optimization of Molecules via Deep Reinforcement Learning".
SUMO Pytorch Deep Reinforcement Learning Traffic Signal Control
Important Note fastrl version 2 is being developed at fastrl. Note the link in the readme
This code is the result of the collaboration of RL Turkey team.
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.
Reinforcement Learning for Optimal inventory policy
Solving Atari Pong Game w/ Duel Double DQN in Pytorch
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.
Implementation of Deep Reinforcement Learning algorithms in the Unity game engine.
Grid-scale li-ion battery optimisation for wholesale market arbitrage, using pytorch implementation of dqn, double dueling dqn and a noisy network dqn.
This project is a pipeline that connects a Matlab simulation (Simulink) to an OpenAI Gym wrapper for PyTorch Reinforcement Learning using the DQN algorithm.
PyTorch implementation of DQN, DDQN and Dueling DQN to solve Atari games including PongNoFrameskip-v4, BreakoutNoFrameskip-v4 and BoxingNoFrameskip-v4
Integrate AutoRL into DQN to implement a single traffic signal control system.
Control Traffic lights intelligently with Reinforcement Learning!
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.
Reinforcement Learning Tutorials & other bedtime stories in PyTorch
Deep Q learning algorithm written on PyTorch for solving 2D robot arm reacher
Reinforcement learning modular with pytorch
Implementation and evaluation of the RL algorithm Rainbow to learn to play Atari games.
Studying emergent communication among agents in cooperative and competitive environments using Reinforcement Learning, game theory and replicator dynamics
This repository provides a customizable ROS2 environment for training multiple 2D drive cars using Deep Q-Network (DQN). Currently, agents learn collision-free navigation by avoiding obstacles, but the environment is designed to allow easy modification to train for various objectives in the future.
Minimum viable reinforcement learning algorithms for your educational convenience.
Implementation of DQN and DDQN algorithms for Playing Car Racing Game
Lunar Lander envitoment of gymnasium solved using Double DQN and D3QN