Challenges when Representing Knowledge in KBS (Knowledge Based Systems)

Challenges during Knowledge Representation

 

Knowledge representation poses several challenges to developers of Knowledge Based Systems (KBS). These challenges include:

 

Choice of knowledge representation language 

It may be difficult to know which Knowledge Representation (KR) language to use especially at the beginning of the development of KBS.

 

Representational and Inferential inadequacy

After choosing a KR language to use in the KBS development, it may turn out to be inadequate in terms of; the ability to represent all of the kinds of knowledge that is needed in a given domain and the ability  to  represent  all  of  the  kinds  of  inferential procedures.

 

Inferential and Acquisitional inefficiency

After choosing a KR language to use, it may turn out to be inefficient in terms of; the ability to represent efficient inference procedures and the ability to acquire new information easily.

 

Complex facts and knowledge structure

Some of the knowledge that requires representation may turn out to be too complex for representation using KR languages. This could make the KR process very costly in terms of time.

 

Complex Knowledge Representation Language

There are different KR languages and the ones best suited to handle structured knowledge representation are complex themselves. If a knowledge engineer is new to a complex KR language, using it may become a problem and may significantly delay the whole process of developing a Knowledge Based System.

 

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Challenges when Representing Knowledge in KBS
Artificial Intelligence | thetqweb