Tutorial EK
Tutorial 1
Q1Data :refers to isolated facts such as individual measurement
Example : • 1.5672 • Mary
INFORMATION :Consists of symbols such as: texts and numbers plus some ‘meaning’ associated with
the symbols
Example: • 10°C • RM1,000,000
KNOWLEDGE : Consist of symbols/notations, the relationships/linkages/connections between
symbols, and rules/procedures for manipulating the relationships
Example: • it’s hot • it’s cold
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decision support systems
advisor systems
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KE is SE applied to the design of KBS , and it’s process of developing knowledge-based
system (KBS).
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Q4Computer scientists • Knowledge specialists • Software engineers • System analysts • Psychologists
• Project managers • Expert in a particular domain (domain experts)
Tutorial 2
Q1Management • Creativity • Analysis capabilities • Verbal skills • Human skills • Fact finding abilities •
Knowledge representation
Q2KBS is a computer system which embodies knowledge about a specific problem domain;
and can thus be used to apply this knowledge to solve problems within that problem domain
Q3Knowledge-based system-A knowledge-based system which is made up of a knowledge base
which is a gathering of knowledge by a human, and stored in the system for decision making.
Types of knowledge-based system- The five types of knowledge-based systems are
1) Expert Systems
2) Hypertext Manipulation Systems
3) CASE Based Systems
4) Database in conjunction with an Intelligent User Interface and
5) Intelligent Tutoring Systems.
Q4Five real time domain to Build the Knowledge Base System- The five real time domain which
is used
to Build the Knowledge Base Systems are
1) Aerospace
2) Communication
3) Medical
4) Process Control
5) Robotics System
Tutorial 3
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Expert system-It is an interactive computer program that is created to make decision like a
human expert and
solve complex problems in a specific domain.It is part of AI and based on facts and heuristics for
solving decision-making problems.
The four activities to transfer knowledge from Expertise to a Computer1) Identification of problem's characterstics.
2) Conceptualisation of rules and the acquiring of the knowledge .
3) Designing of acquisition methodology or architecture.
4) Implementation of knowledge base and the development of a prototype.
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Tutorial 4
Q1Expert System: Expert systems (ES) are one of the prominent research domains of AI. It was
introduced by the researchers at Stanford University, Computer Science Department. The computer
applications developed to solve complex problems in a particular domain, at the level of extraordinary human intelligence and expertise.
Characteristics of Expert Systems include: High performance, Understandable, Reliable and Highly
Responsive.
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Tutorial 5
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