Knowledge representation

Knowledge representation is the formal organization of information so people or computer systems can interpret and use it. It makes knowledge explicit enough for reasoning, retrieval, or computation.

Propositional logic: A formal system that represents statements as propositions combined with logical connectives. It provides a basic language for encoding facts and checking their logical consequences.
Automated reasoning: The use of algorithms to derive conclusions from formal representations of facts and rules. Inference turns encoded knowledge into conclusions not explicitly stored.
Procedural knowledge: Knowledge expressed as procedures or instructions for carrying out tasks. It encodes how to act, unlike declarative representations that state what is true.
Semantic Web: An extension of the Web that uses structured data and linked identifiers to make information machine-interpretable. Its standards publish linked, formally described data across websites.
Knowledge acquisition: The process of obtaining, structuring, and validating knowledge for use in a computational system. Building a representation depends on extracting reliable knowledge from people and sources.
Predicate logic: A formal system that represents objects, properties, relations, and quantified statements. Its predicates and quantifiers express structured facts beyond simple true-or-false propositions.
Description logic: A family of logics for representing concepts, roles, and individuals with decidable reasoning procedures. It balances expressive knowledge modeling with computationally tractable inference.
Declarative programming: A programming style that specifies desired properties or results rather than step-by-step procedures. It separates statements of knowledge from the procedures used to compute with them.
Resource Description Framework: A data model that represents statements as subject–predicate–object triples. RDF supplies a standard graph structure for exchanging linked knowledge on the Web.
Common-sense reasoning: Reasoning with the everyday assumptions and background knowledge people use to interpret situations. Formal systems remain challenged by the vast implicit knowledge people rarely state.

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