Agentic AI-Based Joint Computing and Networking via Mixture of Experts and Large Language Models

This paper proposes an agentic artificial intelligence (AI)-based network optimization framework that integrates mixture of experts (MoE) architectures with large language models (LLMs). The LLM acts as a semantic gate to reason over operator objectives and dynamically compose suitable optimization agents for 6G mobile networks.