Multi Agent Proximal Policy Optimization

Multi-agent proximal policy optimization (MAPPO) is a deep reinforcement learning approach designed to train multiple agents to collaborate effectively on complex tasks. Current research focuses on improving MAPPO's performance and scalability through techniques like attention mechanisms for better credit assignment, graph neural networks for representing agent interactions, and incorporating intent sharing or communication protocols to enhance coordination. These advancements are driving significant improvements in various applications, including traffic control, robotics, and resource management in wireless networks, by enabling more efficient and robust decentralized control systems.

Papers

September 8, 2024

Towards Multi-agent Policy-based Directed Hypergraph Learning for Traffic Signal Control
Kang Wang, Zhishu Shen, Zhenwei Wang, Tiehua Zhang
Deep Reinforcement Learning Traffic Signal Control Graph Learning Task Hypergraph Learning Multi Agent Proximal Policy Optimization

August 29, 2024

Learning Multi-agent Multi-machine Tending by Mobile Robots
Abdalwhab Abdalwhab, Giovanni Beltrame, Samira Ebrahimi Kahou, David St-Onge
LeArning Abstract Multi Agent Reinforcement Learning Mobile Robot Collaborative Robot Multi Agent Environment Multi Agent Proximal Policy Optimization

August 13, 2024

MAPPO-PIS: A Multi-Agent Proximal Policy Optimization Method with Prior Intent Sharing for CAVs' Cooperative Decision-Making
Yicheng Guo, Jiaqi Liu, Rongjie Yu, Peng Hang, Jian Sun
Autonomous Vehicle Multi Agent Reinforcement Learning Multi Agent Proximal Policy Optimization Collaborative Decision Connected and Automated Vehicle Intent Sharing

August 8, 2024

Assigning Credit with Partial Reward Decoupling in Multi-Agent Proximal Policy Optimization
Aditya Kapoor, Benjamin Freed, Howie Choset, Jeff Schneider
Multi Agent Reinforcement Learning Credit Assignment Individual Agent Multi Agent Task Multi Agent Proximal Policy Optimization

March 19, 2024

Graph Neural Network-based Multi-agent Reinforcement Learning for Resilient Distributed Coordination of Multi-Robot Systems
Anthony Goeckner, Yueyuan Sui, Nicolas Martinet, Xinliang Li, Qi Zhu
Multi Agent Reinforcement Learning Multi Robot System Graph Neural Multi Agent Coordination Graph Reinforcement Learning Multi Agent Proximal Policy Optimization

February 5, 2024

Multi-agent Reinforcement Learning for Energy Saving in Multi-Cell Massive MIMO Systems
Tianzhang Cai, Qichen Wang, Shuai Zhang, Özlem Tuğfe Demir, Cicek Cavdar
Multi Agent Reinforcement Learning Energy Efficiency Massive MIMO Multi Agent Proximal Policy Optimization Multi Cell

January 18, 2024

Multi-Agent Reinforcement Learning for Maritime Operational Technology Cyber Security
Alec Wilson, Ryan Menzies, Neela Morarji, David Foster, Marco Casassa Mont, Esin Turkbeyler, Lisa Gralewski
Multi Agent Reinforcement Learning Proximal Policy Optimization Multi Agent Proximal Policy Optimization Maritime Surveillance Autonomous Cyber

January 3, 2024

Optimizing UAV-UGV Coalition Operations: A Hybrid Clustering and Multi-Agent Reinforcement Learning Approach for Path Planning in Obstructed Environment
Shamyo Brotee, Farhan Kabir, Md. Abdur Razzaque, Palash Roy, Md. Mamun-Or-Rashid, Md. Rafiul Hassan, Mohammad Mehedi Hassan
Multi Agent Reinforcement Learning Unmanned Aerial Vehicle Path Planning Unmanned Ground Vehicle Occluded Object Multi Agent Proximal Policy Optimization

December 10, 2023

Multi-Agent Reinforcement Learning for Multi-Cell Spectrum and Power Allocation
Yiming Zhang, Dongning Guo
Multi Agent Reinforcement Learning Task Scheduling Observable Markov Decision Process Interaction Graph Multi Agent Proximal Policy Optimization

November 6, 2023

Imitation Learning based Alternative Multi-Agent Proximal Policy Optimization for Well-Formed Swarm-Oriented Pursuit Avoidance
Sizhao Li, Yuming Xiang, Rongpeng Li, Zhifeng Zhao, Honggang Zhang
Imitation Learning Collision Avoidance Multi Robot System Formation Control Multi Agent Proximal Policy Optimization Conditioned Imitation

September 20, 2023

Safety Guaranteed Robust Multi-Agent Reinforcement Learning with Hierarchical Control for Connected and Automated Vehicles
Zhili Zhang, H M Sabbir Ahmad, Ehsan Sabouni, Yanchao Sun, Furong Huang, Wenchao Li, Fei Miao
Multi Agent Reinforcement Learning Control Barrier Function Safe Reinforcement Learning Robust Policy Connected Autonomous Vehicle Multi Agent Proximal Policy Optimization State Perturbation

August 8, 2023

Communication-Efficient Cooperative Multi-Agent PPO via Regulated Segment Mixture in Internet of Vehicles
Xiaoxue Yu, Rongpeng Li, Fei Wang, Chenghui Peng, Chengchao Liang, Zhifeng Zhao, Honggang Zhang
Multi Agent Reinforcement Learning Vehicle Plan Cooperative Multi Agent Reinforcement Learning Multi Agent Policy Mixed Autonomy Traffic Multi Agent Proximal Policy Optimization Mapping Algorithm Domain Mixture

July 21, 2023

An Analysis of Multi-Agent Reinforcement Learning for Decentralized Inventory Control Systems
Marwan Mousa, Damien van de Berg, Niki Kotecha, Ehecatl Antonio del Rio-Chanona, Max Mowbray
General Analysis Multi Agent Reinforcement Learning Supply Chain Multi Agent Proximal Policy Optimization Inventory Control

May 26, 2023

A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem
Paul Barde, Jakob Foerster, Derek Nowrouzezahrai, Amy Zhang
Multi Agent Reinforcement Learning Action Free Offline Offline Multi Agent Reinforcement Learning Multi Agent Proximal Policy Optimization Coordination Problem

May 23, 2023

Research on Multi-Agent Communication and Collaborative Decision-Making Based on Deep Reinforcement Learning
Zeng Da
Deep Reinforcement Learning Multi Agent Proximal Policy Optimization DH Research Multi Agent Communication Multi Agent Proximal Policy Optimization Collaborative Decision

May 17, 2023

Collective Large-scale Wind Farm Multivariate Power Output Control Based on Hierarchical Communication Multi-Agent Proximal Policy Optimization
Yubao Zhang, Xin Chen, Sumei Gong, Haojie Chen
Multi Agent Proximal Policy Optimization Wind Energy

March 15, 2023

Muti-Agent Proximal Policy Optimization For Data Freshness in UAV-assisted Networks
Mouhamed Naby Ndiaye, El Houcine Bergou, Hajar El Hammouti
Reinforcement Learning Proximal Policy Optimization Policy Reinforcement Learning Cooperative Multi Agent Reinforcement Learning Multi Agent Proximal Policy Optimization Data Quality Issue UAV Assisted

January 6, 2023

Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads
Vincent Mai, Philippe Maisonneuve, Tianyu Zhang, Hadi Nekoei, Liam Paull, Antoine Lesage-Landry
Multi Agent Reinforcement Learning Energy Consumption Multi Agent Communication Demand Response Multi Agent Proximal Policy Optimization Decentralized Agent Frequency Control

November 11, 2022

Efficient Domain Coverage for Vehicles with Second-Order Dynamics via Multi-Agent Reinforcement Learning
Xinyu Zhao, Razvan C. Fetecau, Mo Chen
Reinforcement Learning Multi Agent Reinforcement Learning Second Order Vehicle Plan Multi Agent Proximal Policy Optimization Coverage Control Classical Control MULTI Agent Semantic Coverage

October 31, 2022

Safe and Efficient Manoeuvring for Emergency Vehicles in Autonomous Traffic using Multi-Agent Proximal Policy Optimisation
Leandro Parada, Eduardo Candela, Luis Marques, Panagiotis Angeloudis
Autonomous Vehicle Multi Agent Proximal Policy Optimization Autonomous Traffic Emergency Vehicle

Multi Agent Proximal Policy Optimization

Papers

Towards Multi-agent Policy-based Directed Hypergraph Learning for Traffic Signal Control

Learning Multi-agent Multi-machine Tending by Mobile Robots

MAPPO-PIS: A Multi-Agent Proximal Policy Optimization Method with Prior Intent Sharing for CAVs' Cooperative Decision-Making

Assigning Credit with Partial Reward Decoupling in Multi-Agent Proximal Policy Optimization

Graph Neural Network-based Multi-agent Reinforcement Learning for Resilient Distributed Coordination of Multi-Robot Systems

Multi-agent Reinforcement Learning for Energy Saving in Multi-Cell Massive MIMO Systems

Multi-Agent Reinforcement Learning for Maritime Operational Technology Cyber Security

Optimizing UAV-UGV Coalition Operations: A Hybrid Clustering and Multi-Agent Reinforcement Learning Approach for Path Planning in Obstructed Environment

Multi-Agent Reinforcement Learning for Multi-Cell Spectrum and Power Allocation

Imitation Learning based Alternative Multi-Agent Proximal Policy Optimization for Well-Formed Swarm-Oriented Pursuit Avoidance

Safety Guaranteed Robust Multi-Agent Reinforcement Learning with Hierarchical Control for Connected and Automated Vehicles

Communication-Efficient Cooperative Multi-Agent PPO via Regulated Segment Mixture in Internet of Vehicles

An Analysis of Multi-Agent Reinforcement Learning for Decentralized Inventory Control Systems

A Model-Based Solution to the Offline Multi-Agent Reinforcement Learning Coordination Problem

Research on Multi-Agent Communication and Collaborative Decision-Making Based on Deep Reinforcement Learning

Collective Large-scale Wind Farm Multivariate Power Output Control Based on Hierarchical Communication Multi-Agent Proximal Policy Optimization

Muti-Agent Proximal Policy Optimization For Data Freshness in UAV-assisted Networks

Multi-Agent Reinforcement Learning for Fast-Timescale Demand Response of Residential Loads

Efficient Domain Coverage for Vehicles with Second-Order Dynamics via Multi-Agent Reinforcement Learning

Safe and Efficient Manoeuvring for Emergency Vehicles in Autonomous Traffic using Multi-Agent Proximal Policy Optimisation