Knowledge Representation (KR) in Artificial Intelligence involves techniques to represent information about the world for a machine to understand and process. Common AI techniques include:
- Semantic Networks: Uses nodes (concepts) and edges (relationships) to represent knowledge as a graph structure.
- Frames: Stores data in structures called frames, which are templates for representing entities and their attributes.
- Rules: Employs “if-then” logic to represent cause-effect or condition-action relationships.
- Logic: Uses formal languages like propositional and predicate logic to describe facts and rules.
- Ontologies: Provides a structured framework of knowledge domains, defining entities, attributes, and relationships.
These techniques are foundational for AI tasks like reasoning, decision-making, and problem-solving.
