A knowledge-based system (KBS) is a computer program that reasons and uses a knowledge base to solve complex problems. The term is broad and refers to many different kinds of systems. The one common theme that unites all knowledge based systems is an attempt to represent knowledge explicitly and a reasoning system that allows it to derive new knowledge. Thus, a knowledge-based system has two distinguishing features: a knowledge base and an inference engine.
The first part, the knowledge base, represents facts about the world, often in some form of subsumption ontology (rather than implicitly embedded in procedural code, in the way a conventional computer program does). Other common approaches in addition to a subsumption ontology include frames, conceptual graphs, and logical assertions.
The second part, the inference engine, allows new knowledge to be inferred. Most commonly, it can take the form of IF-THEN rules coupled with forward chaining or backward chaining approaches. Other approaches include the use of automated theorem provers, logic programming, blackboard systems, and term rewriting systems such as CHR (Constraint Handling Rules). These more formal approaches are covered in detail in the Wikipedia article on knowledge representation and reasoning.
Knowledge-based systems were first developed by artificial intelligence researchers. These early knowledge-based systems were primarily expert systems – in fact, the term is often used interchangeably with expert systems, although there is a difference. The difference is in the view taken to describe the system:
"expert system" refers to the type of task the system is trying to assist with – to replace or aid a human expert in a complex task typically viewed as requiring expert knowledge
"knowledge-based system" refers to the architecture of the system – that it represents knowledge explicitly, rather than as procedural code.
While the earliest knowledge-based systems were almost all expert systems, the same tools and architectures can and have since been used for a whole host of other types of systems.
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In information technology a reasoning system is a software system that generates conclusions from available knowledge using logical techniques such as deduction and induction. Reasoning systems play an important role in the implementation of artificial intelligence and knowledge-based systems. By the everyday usage definition of the phrase, all computer systems are reasoning systems in that they all automate some type of logic or decision.
Knowledge engineering (KE) refers to all technical, scientific and social aspects involved in building, maintaining and using knowledge-based systems. One of the first examples of an expert system was MYCIN, an application to perform medical diagnosis. In the MYCIN example, the domain experts were medical doctors and the knowledge represented was their expertise in diagnosis. Expert systems were first developed in artificial intelligence laboratories as an attempt to understand complex human decision making.
Frames are an artificial intelligence data structure used to divide knowledge into substructures by representing "stereotyped situations". They were proposed by Marvin Minsky in his 1974 article "A Framework for Representing Knowledge". Frames are the primary data structure used in artificial intelligence frame languages; they are stored as ontologies of sets. Frames are also an extensive part of knowledge representation and reasoning schemes. They were originally derived from semantic networks and are therefore part of structure-based knowledge representations.
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