Where Streams of Knowledge Converge: Constructing and Optimizing a Hierarchical Intelligent Question-Answering System for Agriculture

TheWith the enhanced use artificial intelligence innovation in farming, it is progressively important to create an intelligent Q&A system with the ability of addressing complicated farming problems. In this paper, we present an intelligent Q&A system for agriculture that incorporates knowledge graph and hierarchical reinforcement learning strategies, in order to boost efficiency through much deeper semantic understanding and even more accurate decision support. The system combines farming data in a detailed knowledge graph, then makes use of hierarchical reinforcement learning to maximize answer generation processes that fulfill transforming farming Q&A requirements. Experimental outcomes demonstrate that this system performs very well in question answering for numerous farming fields, not just enhancing accuracy and importance of solutions yet also efficiently mitigating illusionary impacts usual to large-scale language models consequently substantially increasing user satisfaction