Lecture 7: 17/5/1435 knowledge Representation Lecturer/ Kawther Abas [email protected] 363CS...
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Transcript of Lecture 7: 17/5/1435 knowledge Representation Lecturer/ Kawther Abas [email protected] 363CS...
![Page 1: Lecture 7: 17/5/1435 knowledge Representation Lecturer/ Kawther Abas k.albasheir@sau.edu.sa 363CS – Artificial Intelligence.](https://reader035.fdocuments.us/reader035/viewer/2022062408/56649f295503460f94c43209/html5/thumbnails/1.jpg)
Lecture 7: 17/5/1435
knowledge Representation
Lecturer/ Kawther [email protected]
363CS – Artificial Intelligence
![Page 2: Lecture 7: 17/5/1435 knowledge Representation Lecturer/ Kawther Abas k.albasheir@sau.edu.sa 363CS – Artificial Intelligence.](https://reader035.fdocuments.us/reader035/viewer/2022062408/56649f295503460f94c43209/html5/thumbnails/2.jpg)
Introduction Real knowledge representation and reasoning
systems come in several major varieties. These differ in their intended use, expressivity,
features,… Some major families are
1. Logic programming languages
2. Theorem provers
3. Rule-based or production systems
4. Semantic networks
5. Frame-based representation languages
6. Databases (deductive, relational, object-oriented, etc.)
7. Constraint reasoning systems
8. Description logics
9. Bayesian networks
10. Evidential reasoning
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What is Knowledge?
data – primitive verifiable facts, of any representation. Data reflects current world,often voluminous frequently changing.
information – interpreted dataknowledge – relation among sets of data
(information), that is very often used for further information deduction. Knowledge is (unlike data) general. Knowledge contains information about behaviour of abstract models of the world.
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Data, Information, Data, Information, KnowledgeKnowledge? ?
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DATA
INFORMATION
KNOWLEDGE
WISDOM
Non-algorithmic(heuristic)
Algorithmic
Non-programmable
programmable
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Knowledge Knowledge Representation Representation TechniquesTechniques
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TECHNIQUES
Object-Attribute Value
Frames
Semantic Networks
Logic
Rules
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Object-Attribute-Value Object-Attribute-Value (OAV)(OAV)
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Using fact : “
•Eg: The ball’s color is red (assign red to the ball’s color) The object can be physical (eg: car, books) or abstract (eg: love, hobby).
•The value can be numerical, string or Boolean! It could be either single or multi valued from different attributes and objects.
Used in MYCIN
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OAV Triplets Diagram OAV Triplets Diagram (i)(i)
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Fact :=: “The chair’s color is red and priced at $ 35.00 ”
CHAIR
RED
$ 35.00
Color
Priced
Object Attribute Value
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OAV Triplets Diagram OAV Triplets Diagram (ii)(ii)
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Fact :=: “TIN 313 is a compulsory subject for MSc Int Sys., code for Artificial Intelligence, and taught by Mr Yousef Salahat”
TIN 313
MSc Int. Sys
Mr Yousef Salahat
Compulsory subject
Taught
Artificial Intelligence
Code
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Rules BasedRules Based
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IF condition THEN action statements. (premise (goal antecedent) consequent)
•Example IF “Temperature is hot” THEN “turn on the air-conditioning system”
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Rules Based System (I)Rules Based System (I)
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Rule 1:IF the ball’s color is red THEN I like the ball.
Rule 2:IF I like the ball THEN I will buy the ball.
IF ball’s color = red THEN like = ball
IF like = ball THEN will buy the ball
Ball’s color = red
Like = ball
Will buy = ball
Question: Ball’s color?
Answer: Red1
2
3
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Working Memory
Knowledge Base
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Rules Based System (II)Rules Based System (II)
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•Rule 1: IF x has a sore throat AND suspect bacterial infectionTHEN x has strep throat
•Rule 2:IF x temperature is > 37 cTHEN x has a fever
•Rule 3:IF x has been sick > a monthAND x has a feverTHEN suspect bacterial infection
•Patient’s temperature = 38 c
•Patient has been sick > 2 months
•Patient has a sore throat
•Conclusion ?
Patient has Strep throat
38حرارة المريض
المريض تعبان من شهرين
المريض لديه التهاب حلق
المريض لديه بكتيريا في الحلق
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The Example of Semantic The Example of Semantic Networks (Bird)Networks (Bird)
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FACT : Parrot is a bird. Typically bird has wings and travel by flying. Bird category falls under animal kingdom. All animal requires air to breathe. Ostrich is a bird but travels by walk.
AnimalAnimalBirdBird
WingsWings
ParrotParrot AirAir
OstrichOstrich
WalkWalk
FlyFly
is-a
travel
travel
has
is-a
Breathe
“exceptional handling”
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Frames StructureFrames Structure
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Frame Name: BIRD
Properties:
Color = unknown
Wings = 2
Flies = True
Frame Name: OSTRICH
Properties:
Color = brown/dark
Wings = 2
Flies = False
Class Name: BIRD
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LogicLogic المنطق الرياضي المنطق الرياضي
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•The oldest representation existed
•Implemented using PROLOG, LISP programming language.
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Logical OperatorsLogical Operators
General Name
Formal Name
Symbols
Not Negation
And Conjunction
Or Disjunction
If… Then/Implies
Conditional
If and only if Biconditional
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FactsFacts
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•Artificial intelligence is a computer system
•Cat is an animal
Or combine
•Ahmed mother is married to Khalid father = True
•Cat is human = false
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RulesRules القواعدالقواعد
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•Easy come easy go
•every way has an answer
or
If
• animal give milk it is a mammal
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Predicate Calculus Logic Predicate Calculus Logic (FOPL)(FOPL)
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operator (variables_1, variables_2,…)
EXAMPLES:
COMPUTER_COURSE(ARTIFICIAL_INTELLEGIENCE)
ANIMAL(CAT)
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Mathmatical LogicMathmatical Logic
Meaning Symbol
For All
Exist
NOT
And
OR v
Then
Greater than gt
Less than lt
Greater than or equal ge
Less than or equal le
equal =
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Predicate Calculus Logic Predicate Calculus Logic (FOPL)(FOPL)
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•Example: “She likes chocolate” likes (she, chocolate).
•Universal quantifier (X) to show all object is true [Eg: All students (X (student (X))]
• Existential quantifier (X) to show existence / partial object is true [ Eg: Some people ( X (people (X))]
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The Example of FOPLThe Example of FOPL
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Normal: “If it doesn’t rain today, Ahmad will go to the beach. FOPL: rain( today) go(Ahmad, beach)
Normal: “All volleyball players are tall” FOPL: X (volleyball_player (X) tall (X))
Normal: Some people like durian. FOPL: X (person(X) likes(X, durian))
Normal: Nobody likes wars FOPL: X likes (X, wars)
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Implementing Propositional Implementing Propositional LogicLogic
P Q P Q
T T T
T F F
F T T
F F T
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“IF the battery is dead THEN the car won’t start”
•P = battery is dead & Q = car won’t start
•Battery is dead = T, car won’t start = T
•“Battery not dead” = F, “car will start” = F
•Equivalence to P Q
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Mammals Mammals
PersonPerson
Female Person
Female Person
Male
Person Male
Person
Mariam Mariam Ahmad Ahmad
HasMother
Sister of
Subset of
Member of
Subset-of
Subset-of
Member of
2legs
legs
1
Example:
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Sister_of(Mariam,Ahmed)Legs(Ahmed)=1Member_of(Mariam,Female_Person)
Ahmed frame: : Ahmed
Member of : Male PersonLegs: 1
Has Sister : Mariam
Person frame:Person:
Subset of : MammalLegs: 2
Has Mother : Female Person
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Example
:حالة استثنائيةأحمد له رجال
واحدة بينما لكل البشر رجالن
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ResolutionTheorem. Resolution is sound. Thai
is, all derived formulas are entailed by the given ones
Theorem: Resolution is refutationally complete.
That is, if a clause set is unsatisfiable, then Resolution will derive the empty clause eventually.
If a clause set is unsatisfiable and closed under the application of resolution inference rule then it contains the empty clause.
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