Pertemuan 8 Representing Knowledge Using Rules Matakuliah : T0264/Inteligensia Semu

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Matakuliah
Tahun
Versi
: T0264/Inteligensia Semu
: 2005
:1
Pertemuan 8
Representing Knowledge Using Rules
1
Learning Outcomes
Pada akhir pertemuan ini, diharapkan mahasiswa
akan mampu :
• << TIK-99 >>
• << TIK-99>>
2
Outline Materi
•
•
•
•
•
Materi 1
Materi 2
Materi 3
Materi 4
Materi 5
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6.1 Procedural vs Declarative
Knowledge
Consider the knowledge base :
man(Marcus)
man(Caesar)
person(Cleopatra)
x : man(x)  person(x)
Supose we want to answer the question
y : person(y)
4
6.1 Procedural vs Declarative
Knowledge
We could answer with any one of :
y = Marcus
y = Caesar
y = Cleopatra
Now consider an alternative KB :
man(Marcus)
man(Caesar)
x : man(x)  person(x)
person(Cleopatra)
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6.2 Logic Programming
PROLOG
A PROLOG program is composed of a set of Horn
clauses.
A Horn clause is a clause that has at most one
positive literal.
Examples :
p
p  q
r  s r  s
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6.2 Logic Programming
A Declarative and a Procedural
Representation
A Representation in Logic
x : pet(x)  small(x)  apartmentpet(x)
x : cat(x)  dog(x)  pet(x)
x : poodle(x)  dog(x)  small(x)
poodle(fluffy)
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6.2 Logic Programming
A Representation in PROLOG
apartmentpet(x)
pet(x)
pet(x)
dog(x)
small(x)
poodle(fluffy).
: - pet(x), small(x).
: - cat(x).
: - dog(x).
: - poodle(x).
: - poodle(x).
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6.2 Logic Programming
Answering Question in PROLOG
?- apartmentpet(x).
?- cat(fluffy).
?- cat(mittens).
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6.3 Forward vs Backward
Reasoning
•
Number of start and goal states.
•
Branching factor in each direction.
•
Need to justify reasoning.
•
Triggers for problem solving.
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6.3 Forward vs Backward
Reasoning
Sample or the Rules for Solving the 8Puzzle
Assume the areas of the tray are numbered:
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6.3 Forward vs Backward
Reasoning
Square 1 empty and Square 2 contains tile n 
Square 2 empty and Square 1 contains tile n
Square 1 empty and Square 4 contains tile n 
Square 4 empty and Square 1 contains tile n
Square 2 empty and Square 1 contains tile n 
Square 1 empty and Square 2 contains tile n
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6.3 Forward vs Backward
Reasoning
An Example :
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6.3 Forward vs Backward
Reasoning
A Bad Use of Heuristic Bidirectional
Search
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6.4 Matching
Representation Affects Matching
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6.4 Matching
White pawn at
Square(file e, rank 2)
AND
Square(file e, rank 3) 
move pawn from
is empty
Square(file e, rank 2)
AND
to Square(file e, rank 4)
Square(file e, rank 4)
is empty
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6.4 Matching
Many-to-Many Matching
• The temporal nature of data.
• Structural similarity in rules.
mammal(x) 
feline(x) 
 jaguar(x)
carnivorous(x) 
has-spots(x)
mammal(x) 
feline(x) 
 tiger(x)
carnivorous(x) 
has-stripes(x)
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6.4 Matching
•
Persistance of variable binding
consistency.
son(x,y) 
 grandparent(x,z)
son(y,z)
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6.4 Matching
A Bit of Dialogue with ELIZA
Person:
ELIZA:
Person:
ELIZA:
Person:
ELIZA:
Men are all alike.
In what way?
They’re always bugging us
about something or other.
Can you think of a specific
example?
Well, my boyfriend made me
come here.
Your boyfriend made you come
here.
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6.4 Matching
Person:
ELIZA:
Person:
ELIZA:
Person:
ELIZA:
He says I’m depressed much of
the time.
I am sorry to hear you are
depressed.
It’s true. I am unhappy.
Do you think coming here will help
you not to be unhappy?
I need some help, that much
seems certain.
What would it mean to you if you
got some help?
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6.4 Matching
Person:
ELIZA:
Perhaps I could learn to get along
with my mother.
Tell me more about your family.
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6.4 Matching
Some ELIZA - like rules
(X me Y) 
(X you Y)
(I remember Z)
 (Why do remember X just now ?)
(My {family-member} is Y)
 (Who else in your family is Y)
(X {family-member} Y)
(Tell me more about your family)
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6.4 Matching
Conflict Resolution
• Preferences based on rules
 Rule order
 Prefer special cases over more general
ones
• Preferences based on objects
 Prefer some objects to others
 location in STM
• Preferences based on states
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6.5 Control Knowledge
Syntax for a Control Rule
Under conditions A and B,
Rules that do {not} mention X
{ at all,
in their left-hand side,
in their right-hand side}
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6.5 Control Knowledge
will
{ definitely be useless,
probably be useless
...
probably be especially useful
definitely be especially useful}
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<< CLOSING>>
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