MAGNNET: Multi-Agent Graph Neural Network-based Efficient Task Allocation for Autonomous Vehicles with Deep Reinforcement Learning

4 February 2025

Papers citing "MAGNNET: Multi-Agent Graph Neural Network-based Efficient Task Allocation for Autonomous Vehicles with Deep Reinforcement Learning"

8 / 8 papers shown

Title
Attention-Augmented Inverse Reinforcement Learning with Graph Convolutions for Multi-Agent Task Allocation Huilin Yin Zhikun Yang Linchuan Zhang Daniel Watzenig 51 0 0 07 Apr 2025
Dynamic Subgoal based Path Formation and Task Allocation: A NeuroFleets Approach to Scalable Swarm Robotics Robinroy Peter Lavanya Ratnabala Eugene Yugarajah Andrew Charles Dzmitry Tsetserukou 34 2 0 01 Sep 2024
Graph-based Decentralized Task Allocation for Multi-Robot Target Localization Juntong Peng Hrishikesh Viswanath Kshitij Tiwari Aniket Bera 68 7 0 16 Sep 2023
Research on Multi-Agent Communication and Collaborative Decision-Making Based on Deep Reinforcement Learning Zeng Da 26 2 0 23 May 2023
RTAW: An Attention Inspired Reinforcement Learning Method for Multi-Robot Task Allocation in Warehouse Environments Aakriti Agrawal Amrit Singh Bedi Tianyi Zhou 71 20 0 13 Sep 2022
A Framework for Real-World Multi-Robot Systems Running Decentralized GNN-Based Policies J. Blumenkamp Steven D. Morad Jennifer Gielis Qingbiao Li Amanda Prorok 46 47 0 02 Nov 2021
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning Tabish Rashid Mikayel Samvelyan Christian Schroeder de Witt Gregory Farquhar Jakob N. Foerster Shimon Whiteson 131 1,669 0 30 Mar 2018
Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments Ryan J. Lowe Yi Wu Aviv Tamar J. Harb Pieter Abbeel Igor Mordatch 130 4,468 0 07 Jun 2017