Toward Agentic Optical Networks: A Vision of LLM Agent-Driven Autonomous Lifecycle Management

arXiv:2609.32226 · cs.NI, cs.AI · Submitted 2026-09-26 · Read on arXiv

cs.NI, cs.AI

Submitted: 2026-09-26

Updated: 2026-09-26

Code: https://github.com/google/A2A

Terminology

RAG — 29× in this paper · explained in 3 episodes
Fine-Tuning — 15× in this paper · explained in 5 episodes
Multi-Agent Framework — 13× in this paper · explained in 3 episodes
Hallucination — 12× in this paper · explained in 4 episodes
Core — 10× in this paper · explained in 2 episodes
Digital Twin — 10× in this paper · explained in 5 episodes
Generative AI — 9× in this paper · explained in 2 episodes
Trace — 9× in this paper · explained in 2 episodes
Accuracy — 7× in this paper · explained in 1 episode
Adaptation — 7× in this paper · explained in 1 episode
Multi-agent Collaboration — 7× in this paper · explained in 2 episodes
Redundancy — 7× in this paper · explained in 2 episodes
Reinforcement Learning — 7× in this paper · explained in 4 episodes
Prompt Engineering — 6× in this paper · explained in 4 episodes
Task Decomposition — 6× in this paper · explained in 2 episodes
Transformer — 6× in this paper · explained in 2 episodes
Verification — 6× in this paper · explained in 2 episodes
Adaptability — 5× in this paper · explained in 1 episode
Alignment — 5× in this paper · explained in 1 episode
AI Agents — 4× in this paper · explained in 2 episodes
Consistency — 4× in this paper · explained in 3 episodes
Domain Adaptation — 4× in this paper · explained in 5 episodes
Robustness — 4× in this paper · explained in 5 episodes
Aggregation — 3× in this paper · explained in 1 episode
Multi-Agent System — 3× in this paper · explained in 6 episodes
Parameter-Efficient Fine-Tuning — 3× in this paper · explained in 2 episodes
Agentic AI — 2× in this paper · explained in 1 episode
Few-Shot Learning — 2× in this paper · explained in 4 episodes
Hallucination Mitigation — 2× in this paper · explained in 2 episodes
Initial Data — 2× in this paper · explained in 2 episodes
Instruction Tuning — 2× in this paper · explained in 2 episodes
Multi-agent Collaborative Framework — 2× in this paper · explained in 2 episodes
State Management — 2× in this paper · explained in 3 episodes
Abstraction — 1× in this paper · explained in 1 episode
Agentic Framework — 1× in this paper · explained in 6 episodes
Analyzer — 1× in this paper · explained in 1 episode
Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
Benchmark — 1× in this paper · explained in 2 episodes
Chain-of-Thought (CoT) — 1× in this paper · explained in 4 episodes
Chain-of-Thought (CoT) Prompting — 1× in this paper · explained in 3 episodes
Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
Closed-Loop Control — 1× in this paper · explained in 3 episodes
Clustering — 1× in this paper · explained in 2 episodes
Diagnostic Tools — 1× in this paper · explained in 2 episodes
Foundation Model — 1× in this paper · explained in 3 episodes
Foundation Models — 1× in this paper · explained in 7 episodes
Generalization — 1× in this paper · explained in 13 episodes
Grounding — 1× in this paper · explained in 3 episodes
Human-in-the-Loop — 1× in this paper · explained in 3 episodes
In-Context Learning — 1× in this paper · explained in 4 episodes
Knowledge Graph — 1× in this paper · explained in 7 episodes
Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
Loss of Signal — 1× in this paper
Parameter-Efficient Fine-Tuning (PEFT) — 1× in this paper · explained in 4 episodes
Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
Retrieval Augmented Generation (RAG) — 1× in this paper · explained in 4 episodes
Retrieval-Augmented Generation (RAG) — 1× in this paper · explained in 16 episodes

Terminology

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