MARbLE: Multi-Agent Reinforcement Learning at the Edge for Digital Agriculture

Author:

Boubin Jayson1,Burley Codi2,Han Peida2,Li Bowen2,Porter Barry3,Stewart Christopher2

Affiliation:

1. Binghamton University,Department of Computer Science

2. Ohio State University,Department of Computer Science and Engineering

3. School of Computing and Communications, Lancaster University,UK

Funder

NSF

Publisher

IEEE

Reference62 articles.

1. Networked Multi-Agent Reinforcement Learning in Continuous Spaces

2. Finite-time analysis of distributed td (0) with linear function approximation on multi-agent reinforcement learning;doan;International Conference on Machine Learning,2019

3. Adaptive autonomous UAV scouting for rice lodging assessment using edge computing with deep learning EDANet

4. MapReduce

5. Fully decentralized multi-agent reinforcement learning with networked agents;zhang;Inter-national Conference on Machine Learning,2018

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2. Tsunami: Scalable, Fault Tolerant Coverage Path Planning for UAV Swarms;2024 International Conference on Unmanned Aircraft Systems (ICUAS);2024-06-04

3. Poster: Profiling Edge Resource Demands of Zoom Maneuvers for Autonomous Unmanned Aerial Vehicles;Proceedings of the Eighth ACM/IEEE Symposium on Edge Computing;2023-12-06

4. Computing paradigms for smart farming in the era of drones: a systematic review;Annals of Telecommunications;2023-11-18

5. CAS: Crop Aerial Sensing Simulation in Smart Farming;2023 20th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON);2023-09-11

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