AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
A framework comprising four dimensions—autonomy, efficacy, goal complexity and generality—is proposed for characterizing AI agents, supporting the construction of agentic profiles for the effective governance of different AI agents.
Agentic artificial intelligence (AI)—systems that reason, act, and interact with autonomy and persistence—presents qualitatively new governance challenges compared to traditional large language models. By operating across multimodal environments and pursuing goals without constant human input, agentic AI introduces b...
The term agent in artificial intelligence lacks a standard definition, complicating the evaluation, comparison, and reproducibility of AI agent research. We address this ambiguity through a survey organized around five dimensions of agenticness: environmental interaction, learning and adaptation, autonomy, goal-directe...
The rapid evolution of artificial intelligence (AI) has transformed digital twins (DTs) from passive simulation models into systems that can support perception, reasoning, planning, and coordination, as well as action, in some settings. However, the integration of agentic AI with DTs creates governance challenges invol...
It is argued that agentic AI governance is four problems, not one, each with a mature governing science, and a five-level maturity model with a non-compensatory bottleneck-weighted index and assessment instrument operationalizes CASE as a scientific rather than process maturity model, grounded in production enterprise...
This Perspective introduces the democratic authorization gap, defined as a break or attenuation in the demonstrable chain connecting legally and democratically grounded public authority to actions selected, sequenced, or executed by an AI agent.
A unified, taxonomy-driven, and deployment-oriented survey of agentic AI systems, synthesizing recent advances through a modular reference architecture and a four-dimensional taxonomy that characterizes agents along the axes of autonomy, tool use, collaboration, and safety–governance is presented.
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