4 papers
A Self-Calibrating Agentic AI Framework for Autonomous Edge Resource Allocation
Fin Gentzen, Marla Grunewald, Iulisloi Zacarias +2
Large Language Models (LLMs) are increasingly deployed as autonomous agents, transitioning from static conversational interfaces to dynamic systems capable of complex reasoning, to…
Enhancing Secure Intent-Based Networking with an Agentic AI: The EU Project MARE Approach
Iulisloi Zacarias, Marla Grunewald, Fin Gentzen +2
In the EU project MARE, a novel plane was proposed and used in combination with intent-based networking (IBN), allowing the operator to focus on what, rather than on how. Recently,…
Efficient Self-Learning and Model Versioning for AI-native O-RAN Edge
Mounir Bensalem, Fin Gentzen, Tuck-Wai Choong +3
The AI-native vision of 6G requires Radio Access Networks to train, deploy, and continuously refine thousands of machine learning (ML) models that drive real-time radio network opt…
Effective ML Model Versioning in Edge Networks
Fin Gentzen, Mounir Bensalem, Admela Jukan
Machine learning (ML) models, data and software need to be regularly updated whenever essential version updates are released and feasible for integration. This is a basic but most…