EdgeAgentX: A Novel Framework for Agentic AI at the Edge in Military Communication Networks
人工智能
2025-05-27 v1 机器学习
多智能体系统
摘要
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.
引用
@article{arxiv.2505.18457,
title = {EdgeAgentX: A Novel Framework for Agentic AI at the Edge in Military Communication Networks},
author = {Abir Ray},
journal= {arXiv preprint arXiv:2505.18457},
year = {2025}
}
备注
6 pages, 2 figures