Accessing the GroupSystems tools
The tools are accessed from the Agenda (Which is the control panel),
The agenda offers a rich collection of features to support the session
leader and the group as they work together to accomplish objectives
during a face to face meeting.
The group resources interact with other members of the group.
People People contain the list of participants with background information
for the meeting.
Whiteboard This is a group enabled drawing and annotation tool.
Handouts These are reference materials for group viewing such as a report,
agenda, or spreadsheet file.
Opinion Meter This is a faster, simpler version of the vote tool.
It allows us to quickly determine the group’s opinions.
Briefcase This allows us to access your commonly used applications such as
word processing, calculators, and e mail.
Personal Log This allows us to make notes during a meeting.
Only we can access these notes.
Event Monitor This keeps s informed of new activities and new information in
existing activities.
Expert System [EI]
An expert system is a system that uses human knowledge captured in
a computer to solve problems that ordinarily require human expertise.
General Purpose Problem solver (GPS)
The general purpose problem solver, a procedure developed by Newell
and Simon from their logic theory machine.
GPS attempts to find operations that reduce the difference between a
goal and current states.
Basic Concept of Expert
The basic concepts of expert system revolve around expertise; expert’s
transferring expertly inferencing rules, and explanation capability.
Expertise is the extensive, task specific knowledge acquired from
training, reading and experience.
The following types of knowledge are examples of what expertise
include…
Theories about the problem area.
Rules and procedures regarding the general problem area.
Rules (heuristics) of what to do in a given problem situation.
Global strategies for solving these types of problems.
Meta knowledge – knowledge about knowledge
Fact about the problem area.
Expert
Typically, human expertise includes a constellation of behavior that
involves the following activities.
Recognizing and formulating the problem
Solving the problem quickly and properly
Explain the solution
Learning from solution
Restructuring knowledge
Breaking rules
Determining relevance
Degrading gracefully – awareness of limitation
o Experts would be able to explain the results, learn new thing about the
domain, restructure knowledge whenever needed, break rules
whenever necessary, and determine whether their expertise is
relevant.
o Experts degrade gracefully. "Meaning that as they approach the
boundaries of their knowledge, they gradually become less proficient at
solving problems, but can still develop reasonable solutions".
Transferring Expertise
The objective of an expert system is to transfer expertise from an
expert to a computer system and then on to other humans (non expert)
These processes involve four activities.
1. Knowledge acquisition – from experts or other recourses
2. Knowledge representation – in the computer
3. Knowledge inferencing
4. Knowledge transfer – to the user.
The knowledge is entered in the computer in a component called
knowledge base.
The two types of knowledge are distinguished.
1. Facts 2. Procedures – usually rules
Inferencing
A unique feature of expert system is its ability to reason (Think).
The inferencing is performed in a component called the inference
engine that includes procedures regarding problem solving.
Rules
Most commercial ES are Rule based system.
The knowledge is assorted mainly in the form of rules, as are the
problem solving procedures.
Structure of Expert Systems
ES are composed of two major parts.
1. The development environment
2. Te consultation (runtime) environment
The ES builder o builds the components and put knowledge into the
knowledge base uses the development environment.
The three major components that appear virtually in every expert
system are …
1. The knowledge base
2. Inference engine
3. User interface
In general, though an expert system may contain the following
components…
1) Knowledge acquisition subsystem 5) User interface
2) Knowledge base 6) Blackboard – workplace
3) Inference engine 7) Explanation subsystem – Justifier
4) User
The tools are accessed from the Agenda (Which is the control panel),
The agenda offers a rich collection of features to support the session
leader and the group as they work together to accomplish objectives
during a face to face meeting.
The group resources interact with other members of the group.
People People contain the list of participants with background information
for the meeting.
Whiteboard This is a group enabled drawing and annotation tool.
Handouts These are reference materials for group viewing such as a report,
agenda, or spreadsheet file.
Opinion Meter This is a faster, simpler version of the vote tool.
It allows us to quickly determine the group’s opinions.
Briefcase This allows us to access your commonly used applications such as
word processing, calculators, and e mail.
Personal Log This allows us to make notes during a meeting.
Only we can access these notes.
Event Monitor This keeps s informed of new activities and new information in
existing activities.
Expert System [EI]
An expert system is a system that uses human knowledge captured in
a computer to solve problems that ordinarily require human expertise.
General Purpose Problem solver (GPS)
The general purpose problem solver, a procedure developed by Newell
and Simon from their logic theory machine.
GPS attempts to find operations that reduce the difference between a
goal and current states.
Basic Concept of Expert
The basic concepts of expert system revolve around expertise; expert’s
transferring expertly inferencing rules, and explanation capability.
Expertise is the extensive, task specific knowledge acquired from
training, reading and experience.
The following types of knowledge are examples of what expertise
include…
Theories about the problem area.
Rules and procedures regarding the general problem area.
Rules (heuristics) of what to do in a given problem situation.
Global strategies for solving these types of problems.
Meta knowledge – knowledge about knowledge
Fact about the problem area.
Expert
Typically, human expertise includes a constellation of behavior that
involves the following activities.
Recognizing and formulating the problem
Solving the problem quickly and properly
Explain the solution
Learning from solution
Restructuring knowledge
Breaking rules
Determining relevance
Degrading gracefully – awareness of limitation
o Experts would be able to explain the results, learn new thing about the
domain, restructure knowledge whenever needed, break rules
whenever necessary, and determine whether their expertise is
relevant.
o Experts degrade gracefully. "Meaning that as they approach the
boundaries of their knowledge, they gradually become less proficient at
solving problems, but can still develop reasonable solutions".
Transferring Expertise
The objective of an expert system is to transfer expertise from an
expert to a computer system and then on to other humans (non expert)
These processes involve four activities.
1. Knowledge acquisition – from experts or other recourses
2. Knowledge representation – in the computer
3. Knowledge inferencing
4. Knowledge transfer – to the user.
The knowledge is entered in the computer in a component called
knowledge base.
The two types of knowledge are distinguished.
1. Facts 2. Procedures – usually rules
Inferencing
A unique feature of expert system is its ability to reason (Think).
The inferencing is performed in a component called the inference
engine that includes procedures regarding problem solving.
Rules
Most commercial ES are Rule based system.
The knowledge is assorted mainly in the form of rules, as are the
problem solving procedures.
Structure of Expert Systems
ES are composed of two major parts.
1. The development environment
2. Te consultation (runtime) environment
The ES builder o builds the components and put knowledge into the
knowledge base uses the development environment.
The three major components that appear virtually in every expert
system are …
1. The knowledge base
2. Inference engine
3. User interface
In general, though an expert system may contain the following
components…
1) Knowledge acquisition subsystem 5) User interface
2) Knowledge base 6) Blackboard – workplace
3) Inference engine 7) Explanation subsystem – Justifier
4) User
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