What is knowledge? What are the properties of knowledge representation systems?

Knowledge is a theoretical or practical understanding of a subject or a domain. Knowledge is also the sum of what is currently known.

Knowledge is ―the sum of what is known: the body of truth, information, and principles acquired by mankind.‖ Or, "Knowledge is what I know, Information is what we know."

There are many other definitions such as:

- Knowledge is "information combined with experience, context, interpretation, and reflection. It is a high-value form of information that is ready to apply to decisions and actions." (T. Davenport et al., 1998)

- Knowledge is ―human expertise stored in a person‘s mind, gained through experience, and interaction with the person‘s environment." (Sunasee and Sewery, 2002)

Knowledge consists of information that has been:

– interpreted,

– categorised,

– applied, experienced and revised.

Knowledge representation (KR) is the study of how knowledge about the world can be represented and what kinds of reasoning can be done with that knowledge. Knowledge Representation is the method used to encode knowledge in Intelligent Systems.

The following properties should be possessed by a knowledge representation system.

Representational Adequacy

- the ability to represent the required knowledge;

Inferential Adequacy

- the ability to manipulate the knowledge represented to produce new knowledge corresponding to that inferred from the original;

Inferential Efficiency

- the ability to direct the inferential mechanisms into the most productive directions by storing appropriate guides;

Acquisitional Efficiency

- the ability to acquire new knowledge using automatic methods wherever possible rather than reliance on human intervention.