Knowledge Representation in AI

Knowledge representation in AI involves encoding information about the world in a form that a computer system can utilize to solve complex tasks such as diagnosing a medical condition, understanding natural language, or making decisions. Methods include semantic networks, frames, rules, and ontologies. Effective knowledge representation enables AI systems to reason, learn, and interact intelligently. It encompasses capturing both factual information and the relationships between different concepts, allowing for inference and problem-solving. This foundational aspect of AI bridges raw data and intelligent behavior, facilitating tasks like expert systems, language processing, and robotics.