drl

An elegant PyTorch deep reinforcement learning library.

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

Refer to https://github.com/AcutronicRobotics/gym-gazebo2 for the new version

Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo

Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch

Code for paper "基于多智能体深度强化学习的车联网通信资源分配优化"

Deep Reinforcement Learning for mobile robot navigation in IR-SIM simulation. Using DRL (SAC, TD3, PPO, DDPG) neural networks, a robot learns to navigate to a random goal point in a simulated environment while avoiding obstacles.

Deep Reinforcement Learning (DQN) based Self Driving Car Control with Vehicle Simulator

Courses on Deep Reinforcement Learning (DRL) and DRL papers for recommender systems

Repository for codes of 'Deep Reinforcement Learning'

Curated list for Deep Reinforcement Learning (DRL): software frameworks, models, datasets, gyms, baselines...

Deep Reinforcement Learning (DRL) agents applied to medical images

Deep Reinforcement Learning for Multiobjective Optimization. Code for this paper

This is a reinforcement learning algorithm library. The code takes into account both performance and simplicity, with little dependence.

Ape-X DQN & DDPG with pytorch & tensorboard

Provide full reinforcement learning benchmark on mujoco environments, including ddpg, sac, td3, pg, a2c, ppo, library

A Trading environment base on Gym