Objectives
Autonomous Multi-Agent Architecture
Design and develop a distributed multi-agent Agentic AI architecture capable of autonomously composing, coordinating, and optimising services across the device–edge–cloud continuum, enabling intelligent operation in future Beyond-5G and 6G environments.
Dynamic AI Agent Generation
Develop a unified framework for the dynamic generation, secure onboarding, and lifecycle management of AI agents, allowing specialised agents to be created, deployed, and integrated according to evolving network and service requirements.
Intent-Based Network Intelligence
Develop intelligent agentic tools that translate high-level service intents into autonomous network actions while supporting secure network exposure, proactive cyber protection, self-healing, and resilient operation of both multi-agent systems and future 6G infrastructures.
AgenticOps Framework
Introduce an AgenticOps framework that supports the deployment, orchestration, monitoring, and continuous lifecycle management of multiple LLM-based Agentic AI agents, enabling scalable and trustworthy operation across heterogeneous environments.
Hybrid AI-Native Orchestration
Develop a hybrid AI-native orchestration framework that enables autonomous service workflow composition, intelligent collaboration between distributed agents, and efficient knowledge sharing to support adaptive and context-aware network operation.
Validation Through Real-World Use Cases
Integrate and validate the Agentic6G framework through representative proof-of-concepts and large-scale demonstration activities, showcasing its benefits across telecom network operations and AI-driven vertical applications, including swarm-intelligent robotics.
Impact, Standardisation and Open Source
Maximise the scientific, technological, and societal impact of Agentic6G through dissemination, collaboration with the SNS JU community, contributions to SDOs, and participation in open-source initiatives supporting the future of AI-native 6G networks.