Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

MARL for Autonomous Vehicles

Spectrum sharing in vehicular networks based on multi-agent reinforcement learning, IEEE Journal on Selected Areas in Communications

a modular reinforcement learning library with JAX agents

Implementation of Q-Transformer, Scalable Offline Reinforcement Learning via Autoregressive Q-Functions, out of Google Deepmind

This is a new repo used for training UAV navigation (local path planning) policy using DRL methods.

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…

DSAC-v2; DSAC-T; DASC; Distributional Soft Actor-Critic

A study code for HEVs eco-driving control

A pytorch implementation of Constrained Reinforcement Learning Algorithm, including Constrained Soft Actor Critic (Soft Actor Critic Lagrangian) and Proximal Policy Optimization Lagrangian

Code for Convex Optimization for Long-term Eco-driving of Fuel Cell Hybrid Electric Vehicles on Signalized Corridors

Code for A controllable neural network-based method for optimal energy management of fuel cell hybrid electric vehicles

The environment code for the paper 'Learning-based Eco-driving Strategy Design for Connected Power-split Hybrid Electric Vehicles at Signalized Corridors'

Open code of my published paper: Ecological Driving Framework of Hybrid Electric Vehicle Based on Heterogeneous Multi-Agent Deep Reinforcement Learning

Cooperative Energy Management and Eco-driving of Plug-in Hybrid Electric Vehicle via Multi-agent Reinforcement Learning

Open code of my published paper: Health-considered energy management strategy for fuel cell hybrid electric vehicle based on improved soft actor critic algorithm adopted with Beta policy

Deep reinforcement learning based energy management strategy for hybrid electric vehicle

SUMO CAV deployment scenarios for [Gueriau and Dusparic 2020] paper presented at The 23rd IEEE International Conference on Intelligent Transportation Systems, 2020.

Official code for article "LLMLight: Large Language Models as Traffic Signal Control Agents".

Paper list of multi-agent reinforcement learning (MARL)

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Cooperative control for traffic light signals and connected autonomous vehicles using deep reinforcement learning

This repository contains the code for the paper "UniTSA: A Universal Reinforcement Learning Framework for V2X Traffic Signal Control".

CoLight: Learning Network-level Cooperation for Traffic Signal Control

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

数学建模程序模板包。Mathematical modeling program template package.