Knowledge Representation and Reasoning
Knowledge Representation (KR) is crucial in AI, allowing for the encoding and manipulation of information. The chapter discusses logic-based representations, focusing on Propositional and First-Order Logic, as well as Ontologies and Semantic Networks. These methods help create intelligent systems capable of reasoning and making informed decisions in complex domains.
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Sections
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4.4Ontologies And Semantic Networks
What we have learnt
- Knowledge Representation is a fundamental aspect of Artificial Intelligence.
- Logic provides a formal framework for representing knowledge and deriving conclusions.
- Ontologies and Semantic Networks enhance the representation of complex relationships and concepts.
Key Concepts
- -- Knowledge Representation
- The formal representation and manipulation of knowledge about the world by machines.
- -- LogicBased Representations
- Formal systems used in AI to represent knowledge through syntax and semantics.
- -- Propositional Logic
- A type of logic that represents facts as true or false statements.
- -- FirstOrder Logic
- An extension of propositional logic that includes variables and quantifiers, allowing for more complex expressions.
- -- Ontologies
- Formal specifications of a set of concepts and the relationships between them within a domain.
- -- Semantic Networks
- Graph-based representations that depict concepts as nodes and relationships as edges.
Additional Learning Materials
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