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A Knowledge-based system is a computer program that reasons and uses knowledge to solve complex problems. Knowledge is acquired and represented using various knowledge representation techniques rules, frames and scripts. The basic advantages offered by such system are documentation of knowledge, intelligent decision support, self learning, reasoning and explanation. Knowledge-based systems are systems based on the methods and techniques of Artificial Intelligence. Their core components are:
- knowledge base
- acquisition mechanisms
- inference mechanisms
Knowledge Base Systems (KBS) goes beyond the decision support philosophy to indicate the expert system technology into the decision making framework. Expert Systems (ES) have been the tools and techniques perfected by artificial intelligence (AI) researchers to deduce decision influences based on codification of knowledge. The codification of knowledge use the principles of knowledge representation (part of the large theoretical ideas of knowledge engineering). Typically such codification uses rules like IF-THEN rules to represent logical implications.
While for some authors[who?] expert systems, case-based reasoning systems and neural networks are all particular types of knowledge-based systems, there are others who consider that neural networks are different, and exclude it from this category.
KBS is a frequently used abbreviation for knowledge-based system.
Akerkar RA and Sajja Priti Srinivas:“Knowledge-based systems”, Jones & Bartlett Publishers, Sudbury, MA, USA (2009)]