Pertemuan 13 Weak Slot-and-Filler Structures

1
Pertemuan 13Weak Slot-and-Filler Structures

• Matakuliah T0264/Inteligensia Semu
• Tahun Juli 2006
• Versi 2/2

2
Learning Outcomes

• Pada akhir pertemuan ini, diharapkan mahasiswa
• akan mampu
• ltlt TIK-99 gtgt
• ltlt TIK-99gtgt

3
Outline Materi

• Materi 1
• Materi 2
• Materi 3
• Materi 4
• Materi 5

4
9.2. Frames

• Frame (Bingkai).
• Frame merupakan kumpulan pengetahuan tentang
  suatu obyek tertentu, peristiwa, lokasi, situasi
  atau informasi lainnya.
• Frame memiliki slot yang menggambarkan rincian
  (atribut) dan karakteristik obyek.
• Frame biasanya digunakan untuk merepresentasikan
  pengetahuan yang didasarkan pada karakteristik
  yang sudah dikenal yang merupakan
  pengalaman-pengalaman.

5
Frames

• Dengan menggunakan Frame maka sangat mudah untuk
  membuat inferensi tentang obyek, peristiwa atau
  situasi baru. Hal ini karena Frame menyediakan
  basis pengetahuan yang ditarik dari pengalaman.

6
Frames Transportasi Darat
Alat Transportasi
Transp. Laut
Transp. Darat

Macam Angk Darat
Angk. Tanpa mesin
Slot Mobil

Macam Mobil
Mobil sedan
Mobil minibus

Jenis BBM
Mobil Bensi
Mobi Solar

7
Frames

• A Simplified Frame System
• Person
• isa Mammal
• cardinality 6,000,000.000
• handed Right
• Adult-Male
• isa Person
• cardinality 2,000,000,000
• height 5-10
• ML-Baseball-Player
• Isa Adult-Male
• Cardinality 624
• height 6-1
• bats equal to handed
• batting-average .252
• team
• uniform-color

8
Representing the Class of All Teams as a Metaclass

• Class
• instance Class
• isa Class
• cardinality
• Team
• instance Class
• isa Class
• cardinality the number of teams that exist
• team size each team has a size
• ML-Baseball-Team
• instance Class
• isa Class
• cardinality 26 the number of baseball team
  that exist
• team size 24 default 24 players on team
• manager
• Brooklyn-Dodgers
• instance ML-Baseball-Team
• isa ML-Basball-Plyer
• team size 24

9
Classes and Metaclasses
10
Representing Relationships among Classes
11
Representing Relationships among Classes

• ML-Baseball-Player
• is-covered-by Pitcher, Catcher, Fielder
• American-Leaguer, National-Leaguer
• Pitcher
• isa ML-Baseball-Player
• mutually-disjoint-with Catcher, Fielder
• Catcher
• isa ML-Baseball-Player
• mutually-disjoint-with Pitcher, Fielder
• Fielder
• isa ML-Baseball-Player
• mutually-disjoint-with Pitcher, Catcher
• American-Leaguer
• isa ML-Baseball-Player
• mutually-disjoint-with National-Leaguer
• National-Leaguer
• isa ML-Baseball-Player
• mutually-disjoint-with American-Leaguer
• Three-Finger-Brown

12
Slots as Full-Fledged Objects

• We want to be able to represent and use the
  following properties of slots (attributes or
  relations)
• The classes to which the attribute can be
  attached.
• Constraints on either the type or the value of
  the attribute.
• A value that all instances of a class must have
  by the definition of the class.
• A default value for the attribute.
• Rules for inheriting values for the attribute.

13
Slots as Full-Fledged Objects

• Rules for computing a value separately from
  inheritance.
• An inverse attribute.
• Whether the slots is single-valued or multivalued.

14
Representing Slots as Frames, I
15
Representing Slots as Frame, II

• Slots
• isa Class
• instance Class
• domain
• range
• range-constraint
• definition
• default
• transfers-through
• to-compute
• inverse
• single-valued

16
Representing Slots as Frame, II
manager instance slots domain
ML-Baseball-Team range Person range-constrai
nt ?x(experience x.manager) default
inverse manager-of single-valued TRUE

17
Representing Slots as Frames, III
my-manager
Instance Slot
Domain ML-Baseball-Player
Range Person
Range-constraint ?x(experience x.my-manager)
To-compute ?x (x.team).manager
Single-valued TRUE

Color
Instance Slot
Domain Physical-Object
Range Color-Set
Transfers-through Top-level-part-of
Visual-salience High
Single-valued FALSE
18
Representing Slots as Frames, IV
Uniform-color
Instance Slot
Isa color
Domain Team-player
Range Color-Set
Range-constraint not Pink
Visual-salience High
Single-valued FALSE

Bats
Instance Slot
Domain ML-Baseball-Player
Range Left, Right, Switch
To-compute ?x x.handed
Single-valued TRUE

19
Tangled Hierarchies
Hierarchies that are not trees are called tangled
hierarchies We want to decide whether Fifi can
fly
The correct answer is no
20
Tangled Hierarchies
Determining whether Dick is a pacifist.
Transverse multiple instance link and more than
one answer can be found along the path.
21
More Tangled Hierarchies
22
More Tangled Hierarchies

• In the case of (a), our new algorithm reaches
  Bird (via Pet-Bird) before it reaches Ostrich.
  So it report that Fifi can fly.
• In the case (b), the algorithm reaches Quaker and
  stops without noticing a contradiction.
• The problem is that path length does not always
  corresponds to the level of generality of class.
• The solution to this problem is to base our
  inheritance algorithm not on path length but on
  the notion of inferential distance, which can be
  defined as follows

23
Defining Property Inheritance

• Inferential Distance
• Class1 is closer to Class2 than to Class3 if and
  only if Class1 has an inference path through
  Class2 to Class3 (in other words, Class2 is
  between Class1 and Class3)
• We can now define the result of inheritance as
  follows The set of competing values for a slot
  S in a frame F contains all those values that
• Can be derived from some frame X that is above F
  in
• the isa hierarchy
• Are not contradicted by some frame Y that has a
  shorter
• inferential distance to F than X does

24
Algorithm Property Inheritance

• To retrieve a value V for slot S of an instance F
  do
• Set CANDIDATES to empty.
• Do breadth-first or Dept-first search up the isa
  hierarchy from F, following all instance and isa
  link. At each step, see if a value for S or one
  of its generalizations is stored.
• If a value is found, add it to CANDIDATES and
  terminate that branch of the search.
• If no value is found but there instance or isa
  link upward, follow them.
• Otherwise terminate the branch.

25
Algorithm Property Inheritance

• 3. For each element C of CANDIDATES do
• See if there is any other element of CANDIDATES
  that was derived from a class closer to F than
  the class from which C came.
• If there is, then removed C from CANDIDATES.
• Check the cardinality of CANDIDATES
• If it is 0, then report that no value was found.
• If it is 1, then return the single element of
  CANDIDATES as V.
• If it is greater then 1, report a contradiction.

26
ltlt CLOSINGgtgt

• End of Pertemuan 13
• Good Luck
• For
• Medial Semester Test