AI Systems · Systems and Thinking

Knowledge Representation

Knowledge representation is the deliberate expression of selected concepts, relationships, constraints, sources, uncertainty, and review state in a form that people or tools can inspect. A representation helps organize meaning for a purpose; it is not the represented thing or proof that every recorded claim is true.

Sources & review

How Atlas supports this record.

Atlas uses original Kinesema wording. These public sources support narrow parts of the record; they are not endorsements or proof of claims outside the roles shown below.

Review
Human reviewed
AI assistance
Yes—human reviewed
Last reviewed
2026-08-23

What Is a Knowledge Representation?

Randall Davis, Howard Shrobe, and Peter Szolovits

Used here for
Knowledge representation can serve several roles, including acting as a surrogate for selected aspects of the world, expressing ontological commitments, supporting inference, and providing a medium for human expression.
Source use
Paraphrased from source
Source type
peer-reviewed primary research article

This is a concise first-release record, not a complete course. Examples, terminology, and reviewed connections can grow through later public projections.

Connected concepts

These are reviewed Atlas relationships, not suggestions inferred from page order or visual proximity. Open a boundary only when you want the extra detail.

Connected from

Intermediate Representations

An intermediate representation deliberately expresses selected information so another stage can inspect or use it. That makes it one scoped form of knowledge or program representation.

Connection boundary

Not every knowledge representation is an intermediate program form, and a useful intermediate structure does not represent everything known about its subject.

Connects to

Knowledge Graphs and Relationships

A knowledge graph is one way to represent selected concepts or claims through identified nodes and explicit relationships.

Connection boundary

Not every knowledge representation is a graph, and a graph does not by itself provide a complete ontology or verified truth.

Connects to

Retrieval and Evaluation

Retrieval can select inspectable material from a represented collection, and evaluation can compare the observed selection with a stated expectation.

Connection boundary

Retrieval does not train a model, prove the selected material true, or show that the representation is complete.