Imagen de Portada

L2M-AID: Autonomous Cyber-Physical Defense by Fusing Semantic Reasoning of Large Language Models with Multi-Agent Reinforcement Learning (Preprint)

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Xu, Tianxiang, Wen, Zhichao, Zhao, Xinyu, Wang, Jun, Li, Yan, Liu, Chang
Formato:	Preprint
Publicado:	2025
Materias:	Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Explainable Autonomous Cyber Defense using Adversarial Multi-Agent Reinforcement Learning
por: Zhang, Yiyao, et al.
Publicado: (2026)

Multi-Agent Actor-Critics in Autonomous Cyber Defense
por: Wang, Mingjun, et al.
Publicado: (2024)

GTCN-G: A Residual Graph-Temporal Fusion Network for Imbalanced Intrusion Detection
por: Xu, Tianxiang, et al.
Publicado: (2025)

Large Language Model-Based Reward Design for Deep Reinforcement Learning-Driven Autonomous Cyber Defense
por: Mukherjee, Sayak, et al.
Publicado: (2025)

The Path To Autonomous Cyber Defense
por: Oesch, Sean, et al.
Publicado: (2024)

PoolFlip: A Multi-Agent Reinforcement Learning Security Environment for Cyber Defense
por: Cadet, Xavier, et al.
Publicado: (2025)

Learning to Communicate in Multi-Agent Reinforcement Learning for Autonomous Cyber Defence
por: Contractor, Faizan, et al.
Publicado: (2025)

Automated Cyber Defense with Generalizable Graph-based Reinforcement Learning Agents
por: King, Isaiah J., et al.
Publicado: (2025)

Hierarchical Multi-agent Reinforcement Learning for Cyber Network Defense
por: Singh, Aditya Vikram, et al.
Publicado: (2024)

Quantitative Resilience Modeling for Autonomous Cyber Defense
por: Cadet, Xavier, et al.
Publicado: (2025)

Firewall Regulatory Networks for Autonomous Cyber Defense
por: Duan, Qi, et al.
Publicado: (2025)

Evaluating Reinforcement Learning Agents for Autonomous Cyber Defence
por: Abby Morris, et al.
Publicado: (2025)

Learning Communication Between Heterogeneous Agents in Multi-Agent Reinforcement Learning for Autonomous Cyber Defence
por: Popa, Alex, et al.
Publicado: (2026)

TRACE: A Multi-Agent System for Autonomous Physical Reasoning for Seismology
por: Liu, Feng, et al.
Publicado: (2026)

ACDZero: MCTS Agent for Mastering Automated Cyber Defense
por: Li, Yu, et al.
Publicado: (2026)

Towards Type Agnostic Cyber Defense Agents
por: Galinkin, Erick, et al.
Publicado: (2024)

Large Language Models are Autonomous Cyber Defenders
por: Castro, Sebastián R., et al.
Publicado: (2025)

Framework GNN-AID: Graph Neural Network Analysis Interpretation and Defense
por: Lukyanov, Kirill, et al.
Publicado: (2025)

Knowledge Tagging with Large Language Model based Multi-Agent System
por: Li, Hang, et al.
Publicado: (2024)

AID: Agent Intent from Diffusion for Multi-Agent Informative Path Planning
por: Lew, Jeric, et al.
Publicado: (2025)

KairosAgent: Agentic Time Series Forecasting with Fused Semantic Reasoning
por: Feng, Kun, et al.
Publicado: (2026)

Large Language Model Integration with Reinforcement Learning to Augment Decision-Making in Autonomous Cyber Operations
por: Tholl, Konur, et al.
Publicado: (2025)

Towards Multi-Agent Autonomous Reasoning in Hydrodynamics
por: Zhao, Jinpai, et al.
Publicado: (2026)

Large Language Models are In-context Teachers for Knowledge Reasoning
por: Zhao, Jiachen, et al.
Publicado: (2023)

DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning
por: Guo, Siyuan, et al.
Publicado: (2024)

Hierarchical Adversarially-Resilient Multi-Agent Reinforcement Learning for Cyber-Physical Systems Security
por: Alqithami, Saad
Publicado: (2025)

Autonomous Building Cyber-Physical Systems Using Decentralized Autonomous Organizations, Digital Twins, and Large Language Model
por: Ly, Reachsak, et al.
Publicado: (2024)

Extension-ranking Semantics for Abstract Argumentation Preprint
por: Skiba, Kenneth, et al.
Publicado: (2025)

Designing Robust Cyber-Defense Agents with Evolving Behavior Trees
por: Potteiger, Nicholas, et al.
Publicado: (2024)

Stable Agentic Control: Tool-Mediated LLM Architecture for Autonomous Cyber Defense
por: Prinos, Kerri, et al.
Publicado: (2026)

Multi‐Agent Reinforcement Learning for Cyber Defence Transferability and Scalability
por: Andrew Thomas, et al.
Publicado: (2025)

Sparse Threats, Focused Defense: Criticality-Aware Robust Reinforcement Learning for Safe Autonomous Driving
por: Wei, Qi, et al.
Publicado: (2026)

Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks
por: Xu, Minrui, et al.
Publicado: (2025)

Strategic Cyber Defense via Reinforcement Learning-Guided Combinatorial Auctions
por: Pham, Mai, et al.
Publicado: (2025)

Optimizing Cyber Defense in Dynamic Active Directories through Reinforcement Learning
por: Goel, Diksha, et al.
Publicado: (2024)

Markov Potential Game and Multi-Agent Reinforcement Learning for Autonomous Driving
por: Yan, Huiwen, et al.
Publicado: (2026)

Game-Theoretic Resilience Framework for Cyber-Physical Microgrids using Multi-Agent Reinforcement Learning
por: Niketh, S Krishna, et al.
Publicado: (2025)

HoneyTrap: Deceiving Large Language Model Attackers to Honeypot Traps with Resilient Multi-Agent Defense
por: Li, Siyuan, et al.
Publicado: (2026)

Reinforced Efficient Reasoning via Semantically Diverse Exploration
por: Zhao, Ziqi, et al.
Publicado: (2026)

Defenses at Odds: Measuring and Explaining Defense Conflicts in Large Language Models
por: Meng, Xiangtao, et al.
Publicado: (2026)