An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments

An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities

Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

基于Clash Core 制作的Clash For Linux备份仓库 A Clash For Linux Backup Warehouse Based on Clash Core

Heterogeneous Hierarchical Multi Agent Reinforcement Learning for Air Combat

Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator. Using Twin Delayed Deep Deterministic Policy Gradient (TD3) neural network, a robot learns to navigate to a random g…

Offical implementation of "Deep Directly-Trained Spiking Neural Networks for Object Detection" (ICCV2023)

[RA-Letter 2022] "Reinforcement Learned Distributed Multi-Robot Navigation with Reciprocal Velocity Obstacle Shaped Rewards"

RL Extension Library for Robots, Based on IsaacLab.

2D Gridworld navigation using RL with Hindsight Experience Replay

Implementing obstacle avoidance and path planning for the Pioneer 3-DX robot using Python, PyTorch, and the deep reinforcement learning algorithm REINFORCE in the Webots Simulator.

Reinforcement learning for Robotics with V-Rep

32 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

Deep reinforcement learning

This is a project about deep reinforcement learning autonomous obstacle avoidance algorithm for UAV.

复现一篇在网格环境中使用改进Q-learning进行路径规划的论文

End_to_end learning to control autonomous ship(ROS/Gazebo)

[IROS 2023] Robust Unmanned Surface Vehicle Navigation with Distributional Reinforcement Learning

Deep Reinforcement Learning (RL) algorithms for underwater target tracking with Autonomous Underwater Vehicles (AUV)

Motion Planner Augmented Reinforcement Learning for Robot Manipulation in Obstructed Environments (CoRL 2020)

Autonomous Navigation of UAV using Reinforcement Learning algorithms.

A large-scale benchmark and learning environment.

Biologically-Inspired Neuronal Adaptation Improves Learning in Neural Networks

Robust RL/ADP control for UAVs

ADP implementation of the shallow lakes problem in MATLAB

Approximate dynamic programming (ADP) and Policy gradient (PG) based sequential optimal experimental design (sOED)

Several ADP algorithms code for the data-driven optimal control of linear time-varying systems

Approximate Dynamic Programming exercises from Powell (2011)

Approximate Dynamic Programming assignment solution for a maze environment at ADPRL at TU Munich

ADP