multiagent-reinforcement-learning
There are 198 repositories under multiagent-reinforcement-learning topic.
LantaoYu/MARL-Papers
Paper list of multi-agent reinforcement learning (MARL)
opendilab/DI-engine
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Farama-Foundation/PettingZoo
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
tigerneil/awesome-deep-rl
For deep RL and the future of AI.
cityflow-project/CityFlow
A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
google-deepmind/meltingpot
A suite of test scenarios for multi-agent reinforcement learning.
xuehy/pytorch-maddpg
A pytorch implementation of MADDPG (multi-agent deep deterministic policy gradient)
FLAIROx/JaxMARL
Multi-Agent Reinforcement Learning with JAX
salesforce/warp-drive
Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
TimeBreaker/MARL-papers-with-code
Multi-Agent Reinforcement Learning (MARL) papers with code
ankonzoid/LearningX
Deep & Classical Reinforcement Learning + Machine Learning Examples in Python
TimeBreaker/Multi-Agent-Reinforcement-Learning-papers
Multi-Agent Reinforcement Learning (MARL) papers
TimeBreaker/MARL-resources-collection
A Collection of Multi-Agent Reinforcement Learning (MARL) Resources
jiachenli94/Awesome-Decision-Making-Reinforcement-Learning
A selection of state-of-the-art research materials on decision making and motion planning.
ArnaudFickinger/gym-multigrid
Lightweight multi-agent gridworld Gym environment
rosewang2008/gym-cooking
🏆 gym-cooking: Code for "Too many cooks: Bayesian inference for coordinating multi-agent collaboration", Winner of the CogSci 2020 Computational Modeling Prize in High Cognition, and a NeurIPS 2020 CoopAI Workshop Best Paper.
tjuHaoXiaotian/pymarl3
We extend pymarl2 to pymarl3, equipping the MARL algorithms with permutation invariance and permutation equivariance properties. The enhanced algorithm achieves 100% win rates on SMAC-V1 and superior performance on SMAC-V2.
real-stanford/decentralized-multiarm
[CoRL 2020] Learning a Decentralized Multiarm Motion Planner
Stanford-ILIAD/PantheonRL
PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.
wwxFromTju/deepmind_MAS_enviroment
some Multiagent enviroment in 《Multi-agent Reinforcement Learning in Sequential Social Dilemmas》 and 《Value-Decomposition Networks For Cooperative Multi-Agent Learning》
nsidn98/InforMARL
Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
hsvgbkhgbv/SQDDPG
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''.
gml16/rl-medical
Communicative Multiagent Deep Reinforcement Learning for Anatomical Landmark Detection using PyTorch.
JohannesAck/MATD3implementation
Code for the RL method MATD3 described in the paper "Reducing Overestimation Bias in Multi-Agent Domains Using Double Centralized Critics"
MichelangeloConserva/TotalWarSimulator
Total War Battle simulator for AI research
AlirezaShamsoshoara/Reinforcement_Learning_Team_Q_learnig_MARL_Multi_Agent_UAV_Spectrum_task
A solution for Dynamic Spectrum Management in Mission-Critical UAV Networks using Team Q learning as a Multi-Agent Reinforcement Learning Approach
mit-wu-lab/IntersectionZoo
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
cyoon1729/Multi-agent-reinforcement-learning
Implementation of Multi-Agent Reinforcement Learning algorithm(s). Currently includes: MADDPG
cage-challenge/cage-challenge-4
The TTCP CAGE Challenges are a series of public challenges instigated to foster the development of autonomous cyber defensive agents. This CAGE Challenge 4 (CC4) returns to a defence industry enterprise environment, and introduces a Multi-Agent Reinforcement Learning (MARL) scenario.
pfeinsper/drone-swarm-search
The Drone Swarm Search project provides an environment for SAR missions built on PettingZoo, where agents, represented by drones, are tasked with locating targets identified as shipwrecked individuals.
baskuit/R-NaD
Experimentation with Regularized Nash Dynamics on a GPU accelerated game
hsvgbkhgbv/shapley-q-learning
This repo is the implementation of paper ''SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning''.
ewanlee/ICLR2019-RL-Papers
The Reinforcement-Learning-Related Papers of ICLR 2019
cjm715/mgym
A collection of multi-agent reinforcement learning OpenAI gym environments
Ankur-Deka/Emergent-Multiagent-Strategies
Emergence of complex strategies through multiagent competition
Lauqz/Drone-Swarm-RL-airsim-sb3
Training of Drone Swarms using StableBaselines3, PettingZoo, AirSim and UE4