@techreport{wmz-nmrg-agent-ndt-arch-04,
    number =    {draft-wmz-nmrg-agent-ndt-arch-04},
    type =      {Internet-Draft},
    institution =   {Internet Engineering Task Force},
    publisher = {Internet Engineering Task Force},
    note =      {Work in Progress},
    url =       {https://datatracker.ietf.org/doc/draft-wmz-nmrg-agent-ndt-arch/04/},
    author =    {Qin Wu and Cheng Zhou and Luis M. Contreras and Sai Han and Yong-Geun Hong},
    title =     {{Network Digital Twin and Agentic AI based Architecture for AI driven Network Operations}},
    pagetotal = 39,
    year =      2026,
    month =     may,
    day =       21,
    abstract =  {A Network Digital Twin (NDT) provides a network emulation tool usable for different purposes such as scenario planning, impact analysis, and change management. Agentic AI enables dynamic goal-driven execution and adaptive behavior and closed-loop autonomy. By integrating a Network Digital Twin into network management together with the Agentic AI, it allows the network management activities to take user intent or service requirements as input, automatically assess, model, and refine optimization strategies under realistic conditions but in a risk-free environment. Such environment that operates to meet these types of requirements is said to have AI driven Network Operations. AI driven Network Operations brings together existing technologies such as Agentic AI and Network Digital Twin which may be seen as the use of a toolbox of existing components enhanced with a few new elements. This document describes an architecture for AI driven network operations and shows how these components work together with network digital twin and Agentic AI capabilities. It provides a cookbook of existing technologies to satisfy the architecture and realize intent- based network management to meet the needs of the network service.},
}