Trending repositories for topic multiagent-reinforcement-learning

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

Paper list of multi-agent reinforcement learning (MARL)

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

Paper list of multi-agent reinforcement learning (MARL)

Paper list of multi-agent reinforcement learning (MARL)

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

Multi-Agent Reinforcement Learning (MARL) papers

Multi-Agent Reinforcement Learning with JAX

A suite of test scenarios for multi-agent reinforcement learning.

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...

🏆 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...

Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

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...

Multi-Agent Reinforcement Learning (MARL) papers

Multi-Agent Reinforcement Learning with JAX

🏆 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...

A suite of test scenarios for multi-agent reinforcement learning.

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

Paper list of multi-agent reinforcement learning (MARL)

Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

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

Paper list of multi-agent reinforcement learning (MARL)

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

Multi-Agent Reinforcement Learning with JAX

A suite of test scenarios for multi-agent reinforcement learning.

A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

For deep RL and the future of AI.

Multi-Agent Reinforcement Learning (MARL) papers with code

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.

Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

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 Collection of Multi-Agent Reinforcement Learning (MARL) Resources

Multi-Agent Reinforcement Learning (MARL) papers

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

Experimentation with Regularized Nash Dynamics on a GPU accelerated game

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 R...

🏆 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...

Multi-Agent Reinforcement Learning with JAX

Reading list for adversarial perspective and robustness in deep reinforcement learning.

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.

Experimentation with Regularized Nash Dynamics on a GPU accelerated game

Multi-Agent Reinforcement Learning (MARL) papers with code

Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation

A Collection of Multi-Agent Reinforcement Learning (MARL) Resources

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

Multi-Agent Reinforcement Learning (MARL) papers

A suite of test scenarios for multi-agent reinforcement learning.

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

Paper list of multi-agent reinforcement learning (MARL)

Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

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 R...

For deep RL and the future of AI.

🏆 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

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

Paper list of multi-agent reinforcement learning (MARL)

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

Multi-Agent Reinforcement Learning with JAX

A suite of test scenarios for multi-agent reinforcement learning.

A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

Multi-Agent Reinforcement Learning (MARL) papers with code

For deep RL and the future of AI.

Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation

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...

A Collection of Multi-Agent Reinforcement Learning (MARL) Resources

Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

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...

Lightweight multi-agent gridworld Gym environment

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...

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

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...

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 with JAX

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...

Experimentation with Regularized Nash Dynamics on a GPU accelerated game

Reading list for adversarial perspective and robustness in deep reinforcement learning.

Multi-Agent Reinforcement Learning (MARL) papers with code

Multi-Agent Reinforcement Learning (MARL) papers

A solution for Dynamic Spectrum Management in Mission-Critical UAV Networks using Team Q learning as a Multi-Agent Reinforcement Learning Approach

A Collection of Multi-Agent Reinforcement Learning (MARL) Resources

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

A suite of test scenarios for multi-agent reinforcement learning.

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

PantheonRL is a package for training and testing multi-agent reinforcement learning environments. PantheonRL supports cross-play, fine-tuning, ad-hoc coordination, and more.

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

Lightweight multi-agent gridworld Gym environment

🏆 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...

Total War Battle simulator for AI research