1 Pertemuan 5 Knowledge Representation Issues Matakuliah: T0264/Inteligensia Semu Tahun: 2005 Versi: 1/0

2 Learning Outcomes Pada akhir pertemuan ini, diharapkan mahasiswa akan mampu : >

3 Outline Materi Materi 1 Materi 2 Materi 3 Materi 4 Materi 5

4 4.1 Representations and Mappings Mapping between Facts and Representation

5 Three Representation of a Mutilated Checkerboard

6 Representation of Facts

7 4.2 Approaches to Knowledge Representation Properties of a Representation System Representation adequacy Inferential adequacy Inferential efficiency Acquisitional efficiency

8 Inheritable Knowledge

9 Viewing a Node as a Frame Baseball-Player Isa: Adult-Male bats :(EQUAL handed) height : 6-1 batting-average:.252

Issues in Knowledge Representation Are there any basic attributes of objects ? Are there any basic relationship among objects ? At what level should knowledge be represented ? How should sets be representation ? How should knowledge be accessed ?

Important Attributes

Relationships among Attributes Representing Inverses Reversible representations that ignore focus : Team(Pee-Wee- Reese, Brooklyn-Dodgers) Pairs of focused entities : - one associated with Pee Wee Reese : team = Brooklyn-Dodgers - one associated with Brooklyn Dodgers : team-members = Pee-Wee-Reese,...

Choosing the Granularity of Representation Suppose we are interested in the following fact : John spotted Sue. We could represent this as spotted(agent(John),object(Sue)) Questions : Who spotted Sue ? Did John see Sue ? We could add facts, e.g.: spotted(x,y)  saw(x,y) An alternative representation : saw(agent(John),object(Sue),timespan(briefly))

14 Are There Primitive Concepts ? Marry is Sue ‘s cousin. Marry = daughter(brother(mother(Sue))) Marry = daughter(sister(mother(Sue))) Marry = daughter(brother(father(Sue))) Marry = daughter(sister(father(Sue))) An alternative : Marry = child(sibling(parent(Sue)))

Representing Sets of Objects Intensional and Extensional Representation Extensional : {Earth} Intensional : {x : sun-planet(x)  human-inhabited(x)} {x : sun-planet(x)  nth-farthest-from-sun(x,3)} {x : sun-planet(x)  nth-biggest(x,5) }

Finding the Right Structures as Needed Selecting an Initial Structure Index structures by English words - John flew to New York. He rode in a plane from one place to another. - John flew a kite. * He held a kite that was up in the air. - John flew down the street. * He moved very rapidly. - John flew into a rage. An idiom Index structures by concepts Use one major clue

The Frame Problem A Similarity Net CHAIR TABLESTOOL DESKSIDEBOARD too big, no back BENCH no back,too wide too high, no back no knee room drawers

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