Tag: Knowledge Representation

Knowledge Representation and reasoning (KRR, KR&R, KR²) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning, such as the application of rules or the relations of sets and subsets.

Examples of knowledge representation formalisms include semantic nets, systems architecture, frames, rules, and ontologies. Examples of automated reasoning engines include inference engines, theorem provers, and classifiers.
—Wikipedia, “Knowledge representation and reasoning”

Knowledge Representation where the knowledge acquired is stored and organize in a form that the computer understands.
—ScienceDirect, “Knowledge Representation”

What is a Knowledge Representation? We argue that the notion can best be understood in terms of five distinct roles it plays, each crucial to the task at hand:

1. A Knowledge Representation (KR) is most fundamentally a surrogate, a substitute for the thing itself, used to enable an entity to determine consequences by thinking rather than acting, i.e., by reasoning about the world rather than taking action in it.
2. It is a set of ontological commitments, i.e., an answer to the question: In what terms should I think about the world?
3. It is a fragmentary theory of intelligent reasoning, expressed in terms of three components: (i) the representation’s fundamental conception of intelligent reasoning; (ii) the set of inferences the representation sanctions; and (iii) the set of inferences it recommends.
4. It is a medium for pragmatically efficient computation, i.e., the computational environment in which thinking is accomplished. One contribution to this pragmatic efficiency is supplied by the guidance a representation provides for organizing information so as to facilitate making the recommended inferences.
5. It is a medium of human expression, i.e., a language in which we say things about the world.

—MIT Computer Science and Artificial Intelligence Laboratory, “What is a Knowledge Representation?“