Trending repositories for topic multi-agent-reinforcement-learning

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

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

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 ...

SustainDC is a set of Python environments for Data Center simulation and control using Heterogeneous Multi Agent Reinforcement Learning. Includes customizable environments for workload scheduling, coo...

A collection of MARL benchmarks based on TorchRL

A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

Multi-Agent Constrained Policy Optimisation (MACPO; MAPPO-L).

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"

Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

SustainDC is a set of Python environments for Data Center simulation and control using Heterogeneous Multi Agent Reinforcement Learning. Includes customizable environments for workload scheduling, coo...

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 ...

A collection of MARL benchmarks based on TorchRL

Multi-Agent Constrained Policy Optimisation (MACPO; MAPPO-L).

A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

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"

Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

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

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

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

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

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

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

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 ...

One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)

A collection of MARL benchmarks based on TorchRL

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

SustainDC is a set of Python environments for Data Center simulation and control using Heterogeneous Multi Agent Reinforcement Learning. Includes customizable environments for workload scheduling, coo...

Deep Reinforcement Learning in C#

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"

Lightweight multi-agent gridworld Gym environment

A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

Safe Multi-Agent Isaac Gym benchmark for safe multi-agent reinforcement learning research.

Jax and Torch Multi-Agent SAC on PettingZoo API

Multi-Agent Constrained Policy Optimisation (MACPO; MAPPO-L).

Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II

SustainDC is a set of Python environments for Data Center simulation and control using Heterogeneous Multi Agent Reinforcement Learning. Includes customizable environments for workload scheduling, coo...

Safe Multi-Agent Isaac Gym benchmark for safe multi-agent reinforcement learning research.

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 ...

Jax and Torch Multi-Agent SAC on PettingZoo API

A collection of MARL benchmarks based on TorchRL

Deep Reinforcement Learning in C#

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"

Lightweight multi-agent gridworld Gym environment

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

Multi-Agent Constrained Policy Optimisation (MACPO; MAPPO-L).

A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

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

One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II

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

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

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

A collection of MARL benchmarks based on TorchRL

Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II

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 ...

One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

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"

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.

Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

Unified Reinforcement Learning Framework

A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

Deep Reinforcement Learning in C#

📚 List of Top-tier Conference Papers on Reinforcement Learning (RL)，including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.

Datasets with baselines for offline multi-agent reinforcement learning.

SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning

demo of multi-agent reinforcement learning algorithms, such as ATT-MADDPG (Modelling the Dynamic Joint Policy of Teammates with Attention Multi-Agent DDPG) and NCC-MARL (Neighborhood Cognition Consist...

SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning

applying multi-agent reinforcement learning for highway-merging autonomous vehicles

A collection of MARL benchmarks based on TorchRL

demo of multi-agent reinforcement learning algorithms, such as ATT-MADDPG (Modelling the Dynamic Joint Policy of Teammates with Attention Multi-Agent DDPG) and NCC-MARL (Neighborhood Cognition Consist...

The implementation of ICLR-2023 paper "Discovering Generalizable Multi-agent Coordination Skills from Multi-task Offline Data".

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"

Safe Multi-Agent Isaac Gym benchmark for safe multi-agent reinforcement learning research.

[IROS 2024] EPH: Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding

SustainDC is a set of Python environments for Data Center simulation and control using Heterogeneous Multi Agent Reinforcement Learning. Includes customizable environments for workload scheduling, coo...

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 ...

Jax and Torch Multi-Agent SAC on PettingZoo API

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

Heterogeneous Hierarchical Multi Agent Reinforcement Learning for Air Combat

Datasets with baselines for offline multi-agent reinforcement learning.

Multi Agent Traffic Scenario Gym: A scenario-based training and evaluation framework for CARLA.

Deep Reinforcement Learning in C#

[NeurIPS 2023] The official implementation of "Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization"

Adversarial Reinforcement Learning papers (single-agent setting and multi-agent setting)

Safe Multi-Agent Reinforcement Learning to Make decisions in Autonomous Driving.

Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x

SigmaRL: A Sample-Efficient and Generalizable Multi-Agent Reinforcement Learning Framework for Motion Planning

[IROS 2024] EPH: Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding

Multi Agent Traffic Scenario Gym: A scenario-based training and evaluation framework for CARLA.

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

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

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

One repository is all that is necessary for Multi-agent Reinforcement Learning (MARL)

Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II

ChatArena (or Chat Arena) is a Multi-Agent Language Game Environments for LLMs. The goal is to develop communication and collaboration capabilities of AIs.

A collection of MARL benchmarks based on TorchRL

Unified Reinforcement Learning Framework

🦁 A research-friendly codebase for fast experimentation of multi-agent reinforcement learning in JAX

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 ...

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.

Deep Reinforcement Learning in C#

📚 List of Top-tier Conference Papers on Reinforcement Learning (RL)，including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.

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"

Datasets with baselines for offline multi-agent reinforcement learning.

Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment

Multi-Agent Resource Optimization (MARO) platform is an instance of Reinforcement Learning as a Service (RaaS) for real-world resource optimization problems.

Tutorial4RL: Tutorial for Reinforcement Learning. 强化学习入门教程.

A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm

This repository is for an open-source environment for multi-agent active voltage control on power distribution networks (MAPDN).

SustainDC is a set of Python environments for Data Center simulation and control using Heterogeneous Multi Agent Reinforcement Learning. Includes customizable environments for workload scheduling, coo...

[IROS 2024] EPH: Ensembling Prioritized Hybrid Policies for Multi-agent Pathfinding

Deep Reinforcement Learning in C#

The proceedings of top conference in 2023 on the topic of Reinforcement Learning (RL), including: AAAI, IJCAI, NeurIPS, ICML, ICLR, ICRA, AAMAS and more.

Heterogeneous Hierarchical Multi Agent Reinforcement Learning for Air Combat

A collection of MARL benchmarks based on TorchRL

Datasets with baselines for offline multi-agent reinforcement learning.

Tutorial4RL: Tutorial for Reinforcement Learning. 强化学习入门教程.

[NeurIPS 2023] The official implementation of "Offline Multi-Agent Reinforcement Learning with Implicit Global-to-Local Value Regularization"

applying multi-agent reinforcement learning for highway-merging autonomous vehicles

XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library

Code for the paper "MARL-iDR: Multi-Agent Reinforcement Learning for Incentive-based Residential Demand Response"

A tool for aggregating and plotting MARL experiment data.

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"

demo of multi-agent reinforcement learning algorithms, such as ATT-MADDPG (Modelling the Dynamic Joint Policy of Teammates with Attention Multi-Agent DDPG) and NCC-MARL (Neighborhood Cognition Consist...

iPLAN: Intent-Aware Planning in Heterogeneous Traffic via Distributed Multi-Agent Reinforcement Learning

An open, minimalist Gymnasium environment for autonomous coordination in wireless mobile networks.

Jax and Torch Multi-Agent SAC on PettingZoo API

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 ...

Heterogeneous Multi-Robot Reinforcement Learning