YongzhengCui

YongzhengCui's Stars

• liushunyu/OPT

  [TPAMI] Interaction Pattern Disentangling for Multi-Agent Reinforcement Learning

  Language:Python171

• pytorch/rl

  A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

  Language:Python2.4k319

• facebookresearch/BenchMARL

  A collection of MARL benchmarks based on TorchRL

  Language:Python29542

• proroklab/VectorizedMultiAgentSimulator

  VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

  Language:Python35071

• Genesis-Embodied-AI/RoboGen

  A generative and self-guided robotic agent that endlessly propose and master new skills.

  Language:Python60950

• ventoy/Ventoy

  A new bootable USB solution.

  Language:C63.3k4.1k

• uzh-rpg/rl_vo

  Repository relating to "Reinforcement Learning Meets Visual Odometry" (ECCV, 2024).

  Language:C++20922

• Cognitive-AI-Systems/pogema

  POGEMA stands for Partially-Observable Grid Environment for Multiple Agents. This is a grid-based environment that was specifically designed to be flexible, tunable and scalable. It can be tailored to a variety of PO-MAPF settings.

  Language:Python21024

• AI4Finance-Foundation/ElegantRL

  Massively Parallel Deep Reinforcement Learning. 🔥

  Language:Python3.8k852

• lich14/CDS

  [NeurIPS 2021] CDS achieves remarkable success in challenging benchmarks SMAC and GRF by balancing sharing and diversity.

  Language:Python8419

• jidiai/GRF_MARL

  Google Research Football MARL Benchmark and Research Toolkit

  Language:Python344

• HumanCompatibleAI/overcooked_ai

  A benchmark environment for fully cooperative human-AI performance.

  Language:Jupyter Notebook720154

• FLAIROx/JaxMARL

  Multi-Agent Reinforcement Learning with JAX

  Language:Python44781

• benellis3/pymarl2

  Fine-tuned MARL algorithms on SMAC (100% win rates on most scenarios)

  Language:Python165

• kkkgo/WSL_Switch_Mod

  为wsl2固定IP和网关

  Language:C++295

• tencent-ailab/hok_env

  Honor of Kings AI Open Environment of Tencent

  Language:Python65573

• opendilab/ACE

  [AAAI 2023] Official PyTorch implementation of paper "ACE: Cooperative Multi-agent Q-learning with Bidirectional Action-Dependency".

  Language:Python21710

• combra-lab/spiking-ddpg-mapless-navigation

  Spiking-DDPG trains an SNN for energy-efficient mapless navigation on Intel's Loihi neuromorphic processor.

  Language:Python6911

• PKU-MARL/Multi-Agent-Transformer

  Language:Python34571

• sucaicai4/Unet-series-for-Ultrasound-image-segmentation

  使用Unet系列语义分割模型,对超声波图像进行分割诊断.

  Language:Python368

• oxwhirl/smacv2

  Language:Python22234

• mlech26l/gigastep

  Language:Python683

• chenf-ai/Multi-Agent-Communication-Considering-Representation-Learning

  Language:Python287

• LXXXXR/CACOM

  Code for "Context-aware Communication for Multi-agent Reinforcement Learning"

  Language:Python173

• TonghanWang/NDQ

  Codes accompanying the paper "Learning Nearly Decomposable Value Functions with Communication Minimization" (ICLR 2020)

  Language:Python8116

• NJU-RL/ACORM

  Language:Python254

• zyfsjycc/GoMARL

  Codes of GoMARL accompanying the paper "Automatic Grouping for Efficient Cooperative Multi-Agent Reinforcement Learning"(NeurIPS 2023). GoMARL is a domain-agnostic MARL method that learns automatic grouping for efficient cooperation by promoting intra- and inter-group coordination.

  Language:Python163

• Zhefan-Xu/CERLAB-UAV-Autonomy

  [CMU] A Versatile and Modular Framework Designed for Autonomous Unmanned Aerial Vehicles [UAVs] (C++/ROS/PX4)

  Language:C++32745

• isaac-sim/IsaacLab

  Unified framework for robot learning built on NVIDIA Isaac Sim

  Language:Python2.4k978

• hanruihua/ir-sim

  A python based light weight robot simulator for the intelligent robotics navigation and learning

  Language:Python12115