The document discusses expert systems, which are computer programs designed to solve complex problems by mimicking human expert decision-making using a knowledge base. Key characteristics include high performance, understandability, reliability, and responsiveness, with examples like Dendral and Mycin illustrating their applications in specific domains like chemistry and medicine. The architecture of an expert system includes components such as a knowledge base, fact database, inference engine, user interface, and explanation system to facilitate interaction and derive conclusions.

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Expert System
 An expert system is a computer program that is designed
to solve complex problems and to provide decision-making
abilitylike a human expert.
 It performs this by extracting knowledge from its
knowledge base using the reasoning and inference rules
according to the user queries.
 It solves the most complex issue as an expert by extracting
the knowledge stored in its knowledge base.

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 These systems are designed for a specific domain, such
as medicine, science, etc.
 The performance of an expert system is based on the
expert's knowledge stored in its knowledge base.
 The more knowledge stored in the KB, the more that
system improves its performance.
 One of the common examples of an ES is a suggestion of
spelling errors while typing in the Google search box.
Example of expert system :-
 DENDRAL: It was an artificial intelligenceproject that was
made as a chemical analysisexpert system. It was used in
organic chemistry to detect unknown organic molecules
with the help of their mass spectra and knowledge base of
chemistry.
 MYCIN: It was one of the earliest backward chaining
expert systems that was designed to find the bacteria
causing infectionslike bacteraemia. It was also used for
the recommendationof antibioticsand the diagnosisof
bloodclotting diseases.

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Characteristics of Expert System
 High Performance: The expert system provides high
performance for solving any type of complex problem of a
specific domain with high efficiency and accuracy.
 Understandable: It responds in a way that can be easily
understandableby the user. It can take input in human
language and provides the output in the same way.
 Reliable: It is much reliablefor generating an efficient and
accurate output.
 Highly responsive: ES provides the result for any complex
query within a very short period of time.
#Architecture of Expert System:-

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 knowledge base :- The knowledge base is a type of storage
that stores knowledge acquired from the different experts
of the particulardomain. It is considered as big storage of
knowledge. The more the knowledge base, the more
precise will be the Expert System. It is similarto a database
that containsinformationand rules of a particulardomain
or subject. The knowledge base containsthe specific
domain knowledge that is used by an expert to derive
conclusionsfrom facts.

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 Fact database :-The fact databasecontainsthe case-
specific data that are to be used in a particularcase to
derive a conclusion.In the case of a medical expert
system, this would contain informationthat had been
obtainedabout the patient’scondition.The user of the
expert system interfaces with it through a user interface,
which provides access to the inference engine, the
explanationsystem, and the knowledge-base editor.
 Explanation system :-The explanationsystem provides
informationto the user about how the inference engine
arrived at its conclusions. Thiscan often be essential,
particularlyif the advice being given is of a critical nature,
such as with a medical diagnosissystem. If the system has
used faulty reasoning to arrive at its conclusions, then
the user may be able to see this by examining the data
given by the explanationsystem.
 knowledge-base editor :-The knowledge-base editor
allowsthe user to edit the informationthat is containedin
the knowledge base. The knowledge-base editoris not
usuallymade availableto the end user of the system but is
used by the knowledge engineer or the expert to provide
and update the knowledge that is containedwithin the
system.
 Inference engine:- The inference engine is known as the
brain of the expert system as it is the main processing unit

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of the system. The inference engine is the part of the
system that uses the rules and facts to derive conclusions.
The inference engine will use forward chaining,backward
chaining,or a combinationof the two to make inferences
from the data that are availableto it. There are two types
of inference engine:
 User Interface:-With the help of a user interface, the
expert system interacts with the user, takes queries as an
input in a readable format, and passes it to the inference
engine. After getting the response from the inference
engine, it displaysthe output to the user. In other words, it
is an interface that helps a non-expert user to
communicate with the expert system to find a solution.