A collection of Deep Reinforcement Learning algorithms implemented in tensorflow. Very extensible. High performing DQN implementation.
Solutions to the Deep RL Bootcamp labs
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
Deep Feature Extraction for Sample-Efficient Reinforcement Learning
Implementation of some reinforcement learning algorithms
Atari-DRQN (keras ver.)
Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version
Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
Ape-X DQN & DDPG with pytorch & tensorboard
gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo
gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo
DeepDip, a DRL Gym agent that plays no-press Diplomacy in BANDANA
The source code for the ICPP'19 paper AdaM: An Adaptive Fine-Grained Scheme for Distributed Metadata Management.
Repository for codes of 'Deep Reinforcement Learning'
Add a description, image, and links to the drl topic page so that developers can more easily learn about it.
To associate your repository with the drl topic, visit your repo's landing page and select "manage topics."