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Objectives
• what is an expert system?
• How to setup an expert system
• Understand the components of
an expert system.
• Forward chain and Backward
chain concept.
• Applications of expert systems.
Guess: What is the purpose of this
app?
What is an
expert
system?
Expert systems have been
developed to mimic the
expertise and knowledge of
an expert in a particular
field.
BEHAVES, ADVICES, HELPS
you like a human expert
in the field.
Other
Examples
Components of an expert system
Components of an expert system
Knowledge base
 A database of facts that is stored and accessed to solve problems
and make decisions
Rule base
 A set of rules or logic that is used to apply the knowledge in the
knowledge base to specific problems
Inference engine
 Applies the rules in the rule base to the facts in the knowledge base to
solve problems
Interface  A way for users to interact with the system and provide input
Explanation system
 Provides the users with explanation and reasoning behind decisions or
recommendations
 Gives a percentage probability of the accuracy of its conclusions
Components of Knowledge Base
The knowledge base of an ES is a store of both, factual and
heuristic knowledge.
Factual Knowledge It is the information widely accepted
−
by the Knowledge Engineers and scholars in the task domain.
Heuristic Knowledge It is about practice, accurate
−
judgement, one’s ability of evaluation, and guessing.
Inference Engine
Use of efficient procedures and rules by the Inference Engine
is essential in deducing a correct, flawless solution.
To recommend a solution, the Inference Engine uses the
following strategies −
Forward Chaining
Backward Chaining
• Information needs to be gathered from human
experts or from written sources such as textbooks,
research papers or the internet.
• Information gathered is used to populate the
knowledge base, which needs to be first created.
• A rules base needs to be created; this is made up of a
series of inference rules so that the inference engine
can draw conclusions.
• The inference engine itself needs to be set up; it is a
complex system since it is the main processing
element, making reasoned conclusions from data in
the knowledge base.
• The user interface needs to be developed to allow
the user and the expert system to communicate.
• Once the system is set up, it needs to be fully tested;
this is done by running the system with known
outcomes so that results can be compared and any
changes to the expert system made.
Setting up an expert system
Forward
Chaining
It is a strategy of an expert system to answer the question, “What can
happen next?”
Here, the Inference Engine follows the chain of conditions and derivations and
finally deduces the outcome. It considers all the facts and rules, and sorts them
before concluding to a solution.
This strategy is followed for working on conclusion, result, or effect.
Backward
Chaining
With this strategy, an expert system finds out the answer to the question, “Why this
happened?”
On the basis of what has already happened, the Inference Engine tries to find out which
conditions could have happened in the past for this result. This strategy is followed for
finding
out cause or reason.
Simplification of both the concept
Test your
understandi
ng - Case
Study
Movie recommendation
system
Inputs
Inference engine
Output
Test your understanding - Case Study
Inputs
•Indicate favourite genres / directors / language / actor / reviews
•Rate movies watched (stars/thumbs up, thumbs down etc.)
Test your understanding - Case Study
Inference engine
• Matching similar movies to users history
(based on director/genre/actor/reviews etc.)
• Filtering movies with similar characteristics as
previously watched
• Filtering movies based on what users with
similar tastes have watched/liked
Test your understanding - Case Study
Output •Display a personalised list
of movie
recommendations
Advantages and disadvantages of expert systems
Advantages Disadvantages
 Consistent results
 Faster responses
 Can store large amounts of data
 Unbiased
 Only as good as the data entered
 Responses can be cold and lack
human emotion
 Requires training to use correctly
Exam style questions???????
Expert systems are used by doctors.
a. Describe how an expert system can be used to diagnose
illnesses. [5]
b. Name two other applications of expert systems. [2]
Link : https://docs.google.com/document/d/1MJ5kMQta5BldYihBbzEKmNlrF2nODckdqz
tgHXwQhEg/edit?usp=sharing
Exam style questions???????
a. five of:
An Interactive user interface appears [1]
Questions are asked about the illness [1]
Yes and No type answers to the questions [1]
Answers lead to other questions [1]
The inference engine searches the knowledge base [2]
Using the rules base [1]
Probabilities/possibilities of diagnoses and treatments are displayed [1]
Displays the ways it achieved the solutions/conclusions / explanation [1]
Exam style questions???????
b. two of:
Mineral prospecting [1]
Car engine fault diagnosis [1]
Chess games [1]
Tax queries [1]
Careers recommendations [1]
Movie recommendations on streaming platforms [1]
Exit Ticket – List out at least 5 keywords you have
learnt with one line statement to define them:
Padlet post - link :
https://padlet.com/ranjith8429/expert-system-list
-out-at-least-5-keywords-you-have-learnt-w-u9gc
mpeu4asnlfa7

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expert system for IGCSE students study material

  • 1. Objectives • what is an expert system? • How to setup an expert system • Understand the components of an expert system. • Forward chain and Backward chain concept. • Applications of expert systems.
  • 2. Guess: What is the purpose of this app?
  • 3. What is an expert system? Expert systems have been developed to mimic the expertise and knowledge of an expert in a particular field. BEHAVES, ADVICES, HELPS you like a human expert in the field.
  • 5. Components of an expert system
  • 6. Components of an expert system Knowledge base  A database of facts that is stored and accessed to solve problems and make decisions Rule base  A set of rules or logic that is used to apply the knowledge in the knowledge base to specific problems Inference engine  Applies the rules in the rule base to the facts in the knowledge base to solve problems Interface  A way for users to interact with the system and provide input Explanation system  Provides the users with explanation and reasoning behind decisions or recommendations  Gives a percentage probability of the accuracy of its conclusions
  • 7. Components of Knowledge Base The knowledge base of an ES is a store of both, factual and heuristic knowledge. Factual Knowledge It is the information widely accepted − by the Knowledge Engineers and scholars in the task domain. Heuristic Knowledge It is about practice, accurate − judgement, one’s ability of evaluation, and guessing.
  • 8. Inference Engine Use of efficient procedures and rules by the Inference Engine is essential in deducing a correct, flawless solution. To recommend a solution, the Inference Engine uses the following strategies − Forward Chaining Backward Chaining
  • 9. • Information needs to be gathered from human experts or from written sources such as textbooks, research papers or the internet. • Information gathered is used to populate the knowledge base, which needs to be first created. • A rules base needs to be created; this is made up of a series of inference rules so that the inference engine can draw conclusions. • The inference engine itself needs to be set up; it is a complex system since it is the main processing element, making reasoned conclusions from data in the knowledge base. • The user interface needs to be developed to allow the user and the expert system to communicate. • Once the system is set up, it needs to be fully tested; this is done by running the system with known outcomes so that results can be compared and any changes to the expert system made. Setting up an expert system
  • 10. Forward Chaining It is a strategy of an expert system to answer the question, “What can happen next?” Here, the Inference Engine follows the chain of conditions and derivations and finally deduces the outcome. It considers all the facts and rules, and sorts them before concluding to a solution. This strategy is followed for working on conclusion, result, or effect.
  • 11. Backward Chaining With this strategy, an expert system finds out the answer to the question, “Why this happened?” On the basis of what has already happened, the Inference Engine tries to find out which conditions could have happened in the past for this result. This strategy is followed for finding out cause or reason.
  • 12. Simplification of both the concept
  • 13. Test your understandi ng - Case Study Movie recommendation system Inputs Inference engine Output
  • 14. Test your understanding - Case Study Inputs •Indicate favourite genres / directors / language / actor / reviews •Rate movies watched (stars/thumbs up, thumbs down etc.)
  • 15. Test your understanding - Case Study Inference engine • Matching similar movies to users history (based on director/genre/actor/reviews etc.) • Filtering movies with similar characteristics as previously watched • Filtering movies based on what users with similar tastes have watched/liked
  • 16. Test your understanding - Case Study Output •Display a personalised list of movie recommendations
  • 17. Advantages and disadvantages of expert systems Advantages Disadvantages  Consistent results  Faster responses  Can store large amounts of data  Unbiased  Only as good as the data entered  Responses can be cold and lack human emotion  Requires training to use correctly
  • 18. Exam style questions??????? Expert systems are used by doctors. a. Describe how an expert system can be used to diagnose illnesses. [5] b. Name two other applications of expert systems. [2] Link : https://docs.google.com/document/d/1MJ5kMQta5BldYihBbzEKmNlrF2nODckdqz tgHXwQhEg/edit?usp=sharing
  • 19. Exam style questions??????? a. five of: An Interactive user interface appears [1] Questions are asked about the illness [1] Yes and No type answers to the questions [1] Answers lead to other questions [1] The inference engine searches the knowledge base [2] Using the rules base [1] Probabilities/possibilities of diagnoses and treatments are displayed [1] Displays the ways it achieved the solutions/conclusions / explanation [1]
  • 20. Exam style questions??????? b. two of: Mineral prospecting [1] Car engine fault diagnosis [1] Chess games [1] Tax queries [1] Careers recommendations [1] Movie recommendations on streaming platforms [1]
  • 21. Exit Ticket – List out at least 5 keywords you have learnt with one line statement to define them: Padlet post - link : https://padlet.com/ranjith8429/expert-system-list -out-at-least-5-keywords-you-have-learnt-w-u9gc mpeu4asnlfa7