Using Knowledge

We have briefly mentioned where knowledge is used in AI systems. Let us consider a little further to what applications and how knowledge may be used.

Learning

-- acquiring knowledge. This is more than simply adding new facts to a knowledge base. New data may have to be classified prior to storage for easy retrieval, etc.. Interaction and inference with existing facts to avoid redundancy and replication in the knowledge and and also so that facts can be updated.

Retrieval

-- The representation scheme used can have a critical effect on the efficiency of the method. Humans are very good at it.

Many AI methods have tried to model human (see lecture on distributed reasoning)

Reasoning

-- Infer facts from existing data.

If a system on only knows:

• Miles Davis is a Jazz Musician.
• All Jazz Musicians can play their instruments well.

If things like Is Miles Davis a Jazz Musician? or Can Jazz Musicians play their instruments well? are asked then the answer is readily obtained from the data structures and procedures.

However a question like Can Miles Davis play his instrument well? requires reasoning.

The above are all related. For example, it is fairly obvious that learning and reasoning involve retrieval etc.