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Analysis

This paper proposes a significant shift in cybersecurity from prevention to resilience, leveraging agentic AI. It highlights the limitations of traditional security approaches in the face of advanced AI-driven attacks and advocates for systems that can anticipate, adapt, and recover from disruptions. The focus on autonomous agents, system-level design, and game-theoretic formulations suggests a forward-thinking approach to cybersecurity.
Reference

Resilient systems must anticipate disruption, maintain critical functions under attack, recover efficiently, and learn continuously.

Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 10:32

A-LAMP: Agentic LLM-Based Framework for Automated MDP Modeling and Policy Generation

Published:Dec 12, 2025 04:21
1 min read
ArXiv

Analysis

The article introduces A-LAMP, a framework leveraging Agentic LLMs for automated Markov Decision Process (MDP) modeling and policy generation. This suggests a focus on automating complex decision-making processes. The use of 'Agentic LLM' implies the framework utilizes LLMs with agent-like capabilities, potentially for planning and reasoning within the MDP context. The source being ArXiv indicates this is likely a research paper.
Reference

Research#6G RAN🔬 ResearchAnalyzed: Jan 10, 2026 12:49

Self-Optimizing 6G RAN via Agentic AI and Simulation-in-the-Loop

Published:Dec 8, 2025 06:34
1 min read
ArXiv

Analysis

This research paper explores a promising approach to optimizing 6G Radio Access Networks (RANs) using agentic AI and simulation-in-the-loop workflows. The approach suggests improvements in network performance through continuous learning and adaptation.
Reference

The research focuses on Reflection-Driven Self-Optimization.

Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 07:55

Smart-TCP: An Agentic AI-based Autonomous and Adaptive TCP Protocol

Published:Nov 29, 2025 13:55
1 min read
ArXiv

Analysis

The article introduces Smart-TCP, a new TCP protocol leveraging agentic AI for autonomous and adaptive network management. This suggests a move towards more intelligent and self-optimizing network infrastructure. The use of 'agentic AI' implies a focus on proactive decision-making and learning within the protocol itself, potentially leading to improved performance and resilience compared to traditional TCP implementations. The source being ArXiv indicates this is a research paper, likely detailing the technical aspects, performance evaluations, and potential limitations of Smart-TCP.
Reference