drxlchan Goto Github PK

bark-ml

Gym environments and agents for autonomous driving.

bilevel-optimization-in-coordination-game

code implementation for 'Bi-level Actor-Critic for Multi-agent Coordination'(AAAI2020)

cm3

Cooperative Multi-goal Multi-stage Multi-agent Reinforcement Learning

complexurbanscenarios

copo

[NeurIPS 2021] Official implementation of paper "Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization".

drxlchan.github.io

easy-rl

强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/

frenet-optimal

gcq_source

GCN CAV

marl_cavs

MARL for autonomous vehicles.

metadrive

MetaDrive: Composing Diverse Scenarios for Generalizable Reinforcement Learning

mivecc_with_drl

This is a Multi-intersection Vehicular Cooperative Control (MiVeCC) scheme to enable cooperation among vehicles in a 3*3 unsignalized intersections. we proposed a algorithm combined heuristic-rule and two-stage deep reinforcement learning. The heuristic-rule achieves vehicles across the intersections without collisions. Based on the heuristic-rule, DDPG is used to optimize the collaborative control of vehicles and improve the traffic efficiency. Simulation results show that the proposed algorithm can improve travel efficiency at multiple intersections by up to 4.59 times without collision compared with existing methods.

mixed_autonomy_intersections

[ITSC 2021] Reinforcement Learning for Mixed Autonomy Intersections

pve-mcc_for_unsignalized_intersection

Aiming at the problem of the traffic efficiency of intelligent networked vehicles passing through unsignalized-intersection in the future smart cities, this project proposed a Progressive Value-expectation Estimation Multi-agent Cooperative Control (PVE-MCC) algorithm based on reinforcement learning. The algorithm takes the intelligent networked vehicles as the research object and designed the reward function for the optimization objective from the three aspects of traffic efficiency, safety, and comfort.

pytorch_geometric

Graph Neural Network Library for PyTorch

rl-mpc-lanemerging

Combining Reinforcement Learning with Model Predictive Control for On-Ramp Merging

rlkit

Collection of reinforcement learning algorithms

studies

学习笔记：自然语言处理(NLP)/深度学习(Deep Learning)/机器学习(Machine Learning)/Python/Pytorch

torchgrl

TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments.