Statistics for topic multi-agent-reinforcement-learning
RepositoryStats tracks 584,797 Github repositories, of these 72 are tagged with the multi-agent-reinforcement-learning topic. The most common primary language for repositories using this topic is Python (59).
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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...
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 ...
Multi-Agent Constrained Policy Optimisation (MACPO; MAPPO-L).
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
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)
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 ...
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
Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II
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...
The implementation of ICLR-2023 paper "Discovering Generalizable Multi-agent Coordination Skills from Multi-task Offline Data".
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
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
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