Knowledge representation using logic is a formal approach to encoding information about the world in a structured and interpretable way. It employs logical systems, such as propositional logic and first-order logic, to represent facts, rules, and relationships between entities. Logic-based knowledge representation enables reasoning by applying inference rules to derive new facts from existing ones, ensuring consistency and transparency. This approach is widely used in artificial intelligence, expert systems, and automated reasoning, allowing machines to make informed decisions based on logical deductions.

Knowledge representation in Artificial Intelligence (AI) refers to the methods used to encode information about the world in a format that a computer can process and reason with. It enables AI systems to store, retrieve, and manipulate knowledge to make informed decisions. Common techniques include semantic networks, frames, production rules, and ontologies, each suited for different problem domains. Effective knowledge representation allows AI to perform reasoning, understand natural language, and interact intelligently with humans. It is fundamental to expert systems, natural language processing, and automated decision-making, making AI systems more efficient and capable of solving complex problems.

Techniques of knowledge representation in Artificial Intelligence (AI) define how information is structured and processed for reasoning and decision-making. The main techniques include logical representation, which uses formal logic to express facts and rules; semantic networks, which represent knowledge as interconnected nodes and relationships; frames, which organize knowledge into structured templates with attributes and values; and production rules, which use "if-then" statements for decision-making. Ontologies provide a hierarchical structure of concepts and their relationships, enabling AI to understand context. These techniques help AI systems efficiently store, retrieve, and apply knowledge, making them crucial for expert systems, natural language processing, and intelligent decision-making.

Buy Chapter 3 - Knowledge Representation (ICS 2305) and learn more about the techniques and frameworks for structuring knowledge in Knowledge Based Systems (KBS), including semantic networks, frames, ontologies, and logic-based representations for reasoning and problem-solving.