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Bibliographic Details
Main Author:	Ray, Abir
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Machine Learning Multiagent Systems
Online Access:	https://arxiv.org/abs/2505.18457
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Table of Contents:

This paper introduces EdgeAgentX, a novel framework integrating federated learning (FL), multi-agent reinforcement learning (MARL), and adversarial defense mechanisms, tailored for military communication networks. EdgeAgentX significantly improves autonomous decision-making, reduces latency, enhances throughput, and robustly withstands adversarial disruptions, as evidenced by comprehensive simulations.