There are 53 repositories under multi-agent-reinforcement-learning topic.
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
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.
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
Unified Reinforcement Learning Framework
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:
The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
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.
DI-engine docs (Chinese and English)
Multi-Robot Warehouse (RWARE): A multi-agent reinforcement learning environment
📚 List of Top-tier Conference Papers on Reinforcement Learning (RL),including: NeurIPS, ICML, AAAI, IJCAI, AAMAS, ICLR, ICRA, etc.
Efficient Large-Scale Fleet Management via Multi-Agent Deep Reinforcement Learning
Lightweight multi-agent gridworld Gym environment
PyTorch implements multi-agent reinforcement learning algorithms, including QMIX, Independent PPO, Centralized PPO, Grid Wise Control, Grid Wise Control+PPO, Grid Wise Control+DDPG.
This repository is for an open-source environment for multi-agent active voltage control on power distribution networks (MAPDN).
A collection of MARL benchmarks based on TorchRL
A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.
Multi-Agent Constrained Policy Optimisation (MACPO; MAPPO-L).
Clean implementation of Multi-Agent Reinforcement Learning methods (MADDPG, MATD3, MASAC, MAD4PG) in TensorFlow 2.x
TensorSwarm: A framework for reinforcement learning of robot swarms.
[NeurIPS 2021] Official implementation of paper "Learning to Simulate Self-driven Particles System with Coordinated Policy Optimization".
This is a framework for the research on multi-agent reinforcement learning and the implementation of the experiments in the paper titled by ''Shapley Q-value: A Local Reward Approach to Solve Global Reward Games''.
Learning multi-agent robotic mobile manipulation with deep reinforcement learning
A Simple, Distributed and Asynchronous Multi-Agent Reinforcement Learning Framework for Google Research Football AI.
:battery: Datasets with baselines for offline multi-agent reinforcement learning.