Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
-
Updated
Dec 4, 2020 - Python
Minimal Deep Q Learning (DQN & DDQN) implementations in Keras
Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]
Reinforcement learning tutorials
AI research environment for the Atari 2600 games 🤖.
A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning (DRL) for Mobile Edge Computing (MEC) | This algorithm captures the dynamics of the MEC environment by integrating the Dueling Double Deep Q-Network (D3QN) model with Long Short-Term Memory (LSTM) networks.
Repository for codes of 'Deep Reinforcement Learning'
The implement of all kinds of dqn reinforcement learning with Pytorch
This projects aims to use reinforcement learning algorithms to play the game 2048.
Implementation of Double DQN reinforcement learning for OpenAI Gym environments with PyTorch.
📖 Paper: Deep Reinforcement Learning with Double Q-learning 🕹️
Keras implementation of DQN on ViZDoom environment
Using pytorch to implement DQN / DDQN / Atari DDQN
This code is the result of the collaboration of RL Turkey team.
Parallel training on multiple Deep RL agents with Federated Learning approach to gain higher rewards
Minimal Implementation of Deep RL Algorithms in PyTorch
Using N-step dueling DDQN with PER for playing Pacman game
DDQN inplementation on PLE FlappyBird environment in PyTorch.
Add a description, image, and links to the ddqn topic page so that developers can more easily learn about it.
To associate your repository with the ddqn topic, visit your repo's landing page and select "manage topics."