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TOPIC
KNOWLEDGE REPRESENTATION
What is knowledge?
• facts, information, and skills acquired through
experience or education; the theoretical or
practical understanding of a subject.
• Knowledge = information + rules
• EXAMPLE
• Doctors, managers.
What is Knowledge representation?
• Knowledge representation is a relationship between
two domains.
• Knowledge representation(KR) is the field
of artificial intelligence (AI) that representing
information about the world in a form of computer
system, that can solve complex tasks, such as
diagnosing a medical condition.
TYPES OF
KNOWLEDGE
• There are 5 types of knowledge.
• 1) Procedural k.
• 2) Declarative k.
• 3) Meta k.
• 4) Heuristic k.
• 5) Structural k.
1)Procedural Knowledge
• Gives information/ knowledge about how to
achieve something.
• Describes how to do things provides set of
directions of how to perform certain tasks.
• Procedural knowledge, also known as imperative
knowledge, is the knowledge exercised in the
performance of some task.
• It depends on targets and problems.
• Example
• How to drive a car?
2)Declarative knowledge
• Its about statements that describe a particular
object and its attributes , including some
behavior in relation with it.
• “Can this knowledge be true or false?”
• It is non-procedural, independent of targets
and problem solving.
• Example
• It is sunny today and chemise are red.
3)Meta Knowledge
• It’s a knowledge about knowledge and how to
gain them.
• Example
• The knowledge that blood pressure is more
important for diagnosing a medical condition
than eyes color.
4)Heuristic Knowledge
• Representing knowledge of some expert in a
field or subject.
• Rules of thumb.
• Heuristic Knowledge are sometimes called
shallow knowledge.
• Heuristic knowledge are empirical as opposed
to deterministic.
5)Structural Knowledge
• Describes what relationship exists between
concepts/ objects.
• Describe structure and their relationship.
• Example
• How to various part of car fit together to make
a car, or knowledge structures in term of
concepts, sub concepts and objects.
KNOWLEDGE
REPRESENTATION
• There are multiple approaches and scheme
that comes to mind when we begin to think
about representation.
• 1)Pictures and symbols
• 2)Graphs and network
• 3)Numbers
1)Pictures and symbols
• Pictorial representation are not easily
translate to useful information is computer
because computer can’t interpret pictures
directly with out complex reasoning.
• Through pictures are useful for human
understanding.
2)Graph and network
• Allows relationship between objects to be
incorporated.
• We can represent procedural knowledge using
graphs.
3)Numbers
• Numbers are an integral part of knowledge
representation used by humans.
• Numbers translate easily to computer
representation.
Types of
knowledge
representation
Basically 4 types of knowledge
representation in AI
• 1) Logical representation
• 2) Production rule
• 3) Semantic networks
• 4) Frame representation
1)LOGICAL REPRESENTATION
• In order to give information to agent and get
info without errors in communication.
• Logic is based on truth.
• There are 2 types of LR
• 1)propositional logic(PL)
• 2)first order predicate logic(FOL)
2) PRODUCTION RULE
• Consist of <condition,action>pairs.
• Agent check if a conditions holds then give a
new situation(state).
• Production rule are belong to and same as
propositional logic.
3) SEMENTIC NETWORK
• These represent knowledge in the form of
graphical network.
• Example
• Tom is a cat
• Tom is grey in color
• Tom is mammal
• Tom is owned by sam
Tom
Cat
Sam
Mammal
Grey
Is a
Is a
Color is
Owne
d by
4) FRAME REPRESENTATION
• Frames are record like structures that consist
of a collection of slots or attributes and the
corresponding slot value.
• Slots have names and values called facets.

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knowledge representation in artificial intelligence

  • 2. What is knowledge? • facts, information, and skills acquired through experience or education; the theoretical or practical understanding of a subject. • Knowledge = information + rules • EXAMPLE • Doctors, managers.
  • 3. What is Knowledge representation? • Knowledge representation is a relationship between two domains. • Knowledge representation(KR) is the field of artificial intelligence (AI) that representing information about the world in a form of computer system, that can solve complex tasks, such as diagnosing a medical condition.
  • 5. • There are 5 types of knowledge. • 1) Procedural k. • 2) Declarative k. • 3) Meta k. • 4) Heuristic k. • 5) Structural k.
  • 6. 1)Procedural Knowledge • Gives information/ knowledge about how to achieve something. • Describes how to do things provides set of directions of how to perform certain tasks. • Procedural knowledge, also known as imperative knowledge, is the knowledge exercised in the performance of some task. • It depends on targets and problems. • Example • How to drive a car?
  • 7. 2)Declarative knowledge • Its about statements that describe a particular object and its attributes , including some behavior in relation with it. • “Can this knowledge be true or false?” • It is non-procedural, independent of targets and problem solving. • Example • It is sunny today and chemise are red.
  • 8. 3)Meta Knowledge • It’s a knowledge about knowledge and how to gain them. • Example • The knowledge that blood pressure is more important for diagnosing a medical condition than eyes color.
  • 9. 4)Heuristic Knowledge • Representing knowledge of some expert in a field or subject. • Rules of thumb. • Heuristic Knowledge are sometimes called shallow knowledge. • Heuristic knowledge are empirical as opposed to deterministic.
  • 10. 5)Structural Knowledge • Describes what relationship exists between concepts/ objects. • Describe structure and their relationship. • Example • How to various part of car fit together to make a car, or knowledge structures in term of concepts, sub concepts and objects.
  • 12. • There are multiple approaches and scheme that comes to mind when we begin to think about representation. • 1)Pictures and symbols • 2)Graphs and network • 3)Numbers
  • 13. 1)Pictures and symbols • Pictorial representation are not easily translate to useful information is computer because computer can’t interpret pictures directly with out complex reasoning. • Through pictures are useful for human understanding.
  • 14. 2)Graph and network • Allows relationship between objects to be incorporated. • We can represent procedural knowledge using graphs.
  • 15. 3)Numbers • Numbers are an integral part of knowledge representation used by humans. • Numbers translate easily to computer representation.
  • 17. Basically 4 types of knowledge representation in AI • 1) Logical representation • 2) Production rule • 3) Semantic networks • 4) Frame representation
  • 18. 1)LOGICAL REPRESENTATION • In order to give information to agent and get info without errors in communication. • Logic is based on truth. • There are 2 types of LR • 1)propositional logic(PL) • 2)first order predicate logic(FOL)
  • 19.
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  • 21. 2) PRODUCTION RULE • Consist of <condition,action>pairs. • Agent check if a conditions holds then give a new situation(state). • Production rule are belong to and same as propositional logic.
  • 22. 3) SEMENTIC NETWORK • These represent knowledge in the form of graphical network. • Example • Tom is a cat • Tom is grey in color • Tom is mammal • Tom is owned by sam
  • 24. 4) FRAME REPRESENTATION • Frames are record like structures that consist of a collection of slots or attributes and the corresponding slot value. • Slots have names and values called facets.