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