1 Pertemuan 8 Representing Knowledge Using Rules Matakuliah : T0264/Inteligensia Semu Tahun : 2005 Versi : 1
Feb 25, 2016
1
Pertemuan 8Representing Knowledge Using Rules
Matakuliah : T0264/Inteligensia Semu Tahun : 2005Versi : 1
2
Learning Outcomes
Pada akhir pertemuan ini, diharapkan mahasiswa akan mampu :• << TIK-99 >>• << TIK-99>>
3
Outline Materi
• Materi 1• Materi 2• Materi 3• Materi 4• Materi 5
4
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 questiony : person(y)
5
6.1 Procedural vs Declarative Knowledge
We could answer with any one of :y = Marcusy = Caesary = Cleopatra
Now consider an alternative KB :man(Marcus)man(Caesar)x : man(x) person(x)person(Cleopatra)
6
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 qr s r s
7
6.2 Logic Programming
A Declarative and a Procedural Representation
A Representation in Logicx : pet(x) small(x) apartmentpet(x)x : cat(x) dog(x) pet(x)x : poodle(x) dog(x) small(x)poodle(fluffy)
8
6.2 Logic Programming
A Representation in PROLOG
apartmentpet(x) : - pet(x), small(x).pet(x) : - cat(x).pet(x) : - dog(x).dog(x) : - poodle(x).small(x) : - poodle(x).poodle(fluffy).
9
6.2 Logic Programming
Answering Question in PROLOG
?- apartmentpet(x).
?- cat(fluffy).
?- cat(mittens).
10
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.
11
6.3 Forward vs Backward Reasoning
Sample or the Rules for Solving the 8-Puzzle
Assume the areas of the tray are numbered:
12
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
13
6.3 Forward vs Backward Reasoning
An Example :
14
6.3 Forward vs Backward Reasoning
A Bad Use of Heuristic Bidirectional Search
15
6.4 Matching
Representation Affects Matching
16
6.4 Matching
White pawn at Square(file e, rank 2)
ANDSquare(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
17
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)
18
6.4 Matching
• Persistance of variable binding consistency.son(x,y)
grandparent(x,z)son(y,z)
19
6.4 Matching
A Bit of Dialogue with ELIZAPerson: Men are all alike.ELIZA: In what way? Person: They’re always bugging us
about something or other. ELIZA: Can you think of a specific
example? Person: Well, my boyfriend made me
come here. ELIZA: Your boyfriend made you come
here.
20
6.4 Matching
Person: He says I’m depressed much of the time.
ELIZA: I am sorry to hear you are depressed.
Person: It’s true. I am unhappy. ELIZA: Do you think coming here will help
you not to be unhappy? Person: I need some help, that much
seems certain. ELIZA: What would it mean to you if you
got some help?
21
6.4 Matching
Person: Perhaps I could learn to get along with my mother.
ELIZA: Tell me more about your family.
22
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)
23
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
24
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}
25
6.5 Control Knowledge
will{ definitely be useless, probably be useless ... probably be especially useful definitely be especially useful}
26
<< CLOSING>>