Trending repositories for topic multiagent-reinforcement-learning
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
A suite of test scenarios for multi-agent reinforcement learning.
Multi-Agent Reinforcement Learning (MARL) papers
Multi-Agent Reinforcement Learning (MARL) papers
A suite of test scenarios for multi-agent reinforcement learning.
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
A suite of test scenarios for multi-agent reinforcement learning.
Multi-Agent Reinforcement Learning (MARL) papers
Lightweight multi-agent gridworld Gym environment
A suite of test scenarios for multi-agent reinforcement learning.
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
Multi-Agent Reinforcement Learning (MARL) papers
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
A suite of test scenarios for multi-agent reinforcement learning.
Multi-Agent Reinforcement Learning (MARL) papers
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
Multi-Agent Reinforcement Learning (MARL) papers with code
Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
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 enterpri...
[CoRL 2020] Learning a Decentralized Multiarm Motion Planner
A Collection of Multi-Agent Reinforcement Learning (MARL) Resources
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...
PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.
Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
Emergence of complex strategies through multiagent competition
some Multiagent enviroment in 《Multi-agent Reinforcement Learning in Sequential Social Dilemmas》 and 《Value-Decomposition Networks For Cooperative Multi-Agent Learning》
🏆 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 C...
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
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 enterpri...
Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
Multi-Agent Reinforcement Learning (MARL) papers
A suite of test scenarios for multi-agent reinforcement learning.
[CoRL 2020] Learning a Decentralized Multiarm Motion Planner
Emergence of complex strategies through multiagent competition
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...
PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Multi-Agent Reinforcement Learning (MARL) papers with code
A Collection of Multi-Agent Reinforcement Learning (MARL) Resources
Lightweight multi-agent gridworld Gym environment
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
some Multiagent enviroment in 《Multi-agent Reinforcement Learning in Sequential Social Dilemmas》 and 《Value-Decomposition Networks For Cooperative Multi-Agent Learning》
Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
🏆 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 C...
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 enterpri...
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
A suite of test scenarios for multi-agent reinforcement learning.
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Multi-Agent Reinforcement Learning (MARL) papers with code
A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario
Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
A Collection of Multi-Agent Reinforcement Learning (MARL) Resources
Multi-Agent Reinforcement Learning (MARL) papers
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...
Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)
Lightweight multi-agent gridworld Gym environment
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 enterpri...
Reading list for adversarial perspective and robustness in deep reinforcement learning.
🏆 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 C...
IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning
PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.
A solution for Dynamic Spectrum Management in Mission-Critical UAV Networks using Team Q learning as a Multi-Agent Reinforcement Learning Approach
[CoRL 2020] Learning a Decentralized Multiarm Motion Planner
Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
UAV-based Cellular-Communication: Multi-Agent Deep Reinforcement Learning for Interference Management
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...
Reading list for adversarial perspective and robustness in deep reinforcement learning.
A solution for Dynamic Spectrum Management in Mission-Critical UAV Networks using Team Q learning as a Multi-Agent Reinforcement Learning Approach
Multi-Agent Reinforcement Learning (MARL) papers with code
Experimentation with Regularized Nash Dynamics on a GPU accelerated game
A Collection of Multi-Agent Reinforcement Learning (MARL) Resources
Multi-Agent Reinforcement Learning (MARL) papers
This repo is the implementation of paper ''SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning''.
IMP-MARL: a Suite of Environments for Large-scale Infrastructure Management Planning via MARL
A suite of test scenarios for multi-agent reinforcement learning.
Lightweight multi-agent gridworld Gym environment
An API standard for multi-agent reinforcement learning environments, with popular reference environments and related utilities
PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.
🏆 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 C...
[CoRL 2020] Learning a Decentralized Multiarm Motion Planner
Communicative Multiagent Deep Reinforcement Learning for Anatomical Landmark Detection using PyTorch.
Emergence of complex strategies through multiagent competition