Tag: RAG-LLM

Intelligent Fish Control: Integrating RAG-LLM and Deep Q-Networks for Enhanced Aquaculture

This article details a novel framework that integrates Retrieval-Augmented Generation Large Language Models (RAG-LLM) with Deep Q-Networks (DQN) to create an intelligent, autonomous system for fish farming. By leveraging IoT devices for real-time monitoring and combining the strengths of LLMs for knowledge retrieval with DQN for optimal policy learning, this system significantly enhances efficiency, productivity, and sustainability in aquaculture, outperforming traditional expert-led methods.