Knowledge Based System

Knowledge-based systems (KBS) aim to build computer systems that can reason and solve problems using explicitly represented knowledge, moving beyond purely statistical approaches. Current research focuses on improving knowledge acquisition and representation, particularly leveraging large language models (LLMs) through techniques like retrieval-augmented generation (RAG) and fine-tuning, as well as enhancing knowledge graph reasoning with reinforcement learning. These advancements are crucial for building more reliable and explainable AI systems across diverse domains, including healthcare, business process management, and scientific literature analysis, leading to improved decision-making and automation.