structured knowledge

43
Structured Knowledge Chapter 7

Upload: gannon-hebert

Post on 01-Jan-2016

47 views

Category:

Documents


1 download

DESCRIPTION

Structured Knowledge. Chapter 7. Logic Notations. Does logic represent well knowledge in structures?. P(x). x. Logic Notations. Frege’s Begriffsschrift (concept writing) - 1879: assert P not P if P then Q for every x, P(x). P. P. Q. P. Logic Notations. - PowerPoint PPT Presentation

TRANSCRIPT

Page 1: Structured Knowledge

Structured Knowledge

Chapter 7

Page 2: Structured Knowledge

2

Logic Notations

Does logic represent well knowledge in structures?

Page 3: Structured Knowledge

3

Logic Notations

Frege’s Begriffsschrift (concept writing) - 1879:

assert P

not P

if P then Q

for every x, P(x)

P

P

Q

PP(x)x

Page 4: Structured Knowledge

4

Logic Notations

Frege’s Begriffsschrift (concept writing) - 1879:

“Every ball is red”

“Some ball is red”

red(x)xball(x)

red(x)xball(x)

Page 5: Structured Knowledge

5

Logic Notations

Algebraic notation - Peirce, 1883:

Universal quantifier: xPx

Existential quantifier: xPx

Page 6: Structured Knowledge

6

Logic Notations

Algebraic notation - Peirce, 1883:

“Every ball is red”: x(ballx — redx)

“Some ball is red”: x(ballx • redx)

Page 7: Structured Knowledge

7

Logic Notations

Peano’s and later notation:

“Every ball is red”: (x)(ball(x) red(x))

“Some ball is red”: (x)(ball(x) red(x))

Page 8: Structured Knowledge

8

Logic Notations

Existential graphs - Peirce, 1897:

Existential quantifier: a link structure of bars, called line of

identity, represents

Conjunction: the juxtaposition of two graphs represents

Negation: an oval enclosure represents ~

Page 9: Structured Knowledge

9

Logic Notations

“If a farmer owns a donkey, then he beats it”:

farmer

owns donkey

beats

Page 10: Structured Knowledge

10

Logic Notations

EG’s rules of inferences:

Erasure: in a positive context, any graph may be erased.

Insertion: in a negative context, any graph may be inserted.

Iteration: a copy of a graph may be written in the same context or any nested context.

Deiteration: any graph may be erased if a copy of its occurs in the same context or a containing context.

Double negation: two negations with nothing between them may be erased or inserted.

Page 11: Structured Knowledge

11

Existential Graphs

Prove: ((p r) (q s)) ((p q) (r s)) is valid

Page 12: Structured Knowledge

12

Existential Graphs

Prove: ((p r) (q s)) ((p q) (r s)) is valid

rp sq

p q

r s

Page 13: Structured Knowledge

13

Existential GraphsProve: ((p r) (q s)) ((p q) (r s))

Erasure: in a positive context, any graph may be erased.

Insertion: in a negative context, any graph may be inserted.

Iteration: a copy of a graph may be written in the same context or any nested context.

Deiteration: any graph may be erased if a copy of its occurs in the same context or a containing context.

Double negation: two negations with nothing between them may be erased or inserted.

Page 14: Structured Knowledge

14

Existential GraphsProve: ((p r) (q s)) ((p q) (r s))

Erasure: in a positive context, any graph may be erased.

Insertion: in a negative context, any graph may be inserted.

Iteration: a copy of a graph may be written in the same context or any nested context.

Deiteration: any graph may be erased if a copy of its occurs in the same context or a containing context.

Double negation: two negations with nothing between them may be erased or inserted.

rp sq

Page 15: Structured Knowledge

15

Existential GraphsProve: ((p r) (q s)) ((p q) (r s))

Erasure: in a positive context, any graph may be erased.

Insertion: in a negative context, any graph may be inserted.

Iteration: a copy of a graph may be written in the same context or any nested context.

Deiteration: any graph may be erased if a copy of its occurs in the same context or a containing context.

Double negation: two negations with nothing between them may be erased or inserted.

rp sq

rp sq

rp

Page 16: Structured Knowledge

16

Existential GraphsProve: ((p r) (q s)) ((p q) (r s))

Erasure: in a positive context, any graph may be erased.

Insertion: in a negative context, any graph may be inserted.

Iteration: a copy of a graph may be written in the same context or any nested context.

Deiteration: any graph may be erased if a copy of its occurs in the same context or a containing context.

Double negation: two negations with nothing between them may be erased or inserted.

rp sq

rp

rp sq

rp q

Page 17: Structured Knowledge

17

Existential GraphsProve: ((p r) (q s)) ((p q) (r s))

Erasure: in a positive context, any graph may be erased.

Insertion: in a negative context, any graph may be inserted.

Iteration: a copy of a graph may be written in the same context or any nested context.

Deiteration: any graph may be erased if a copy of its occurs in the same context or a containing context.

Double negation: two negations with nothing between them may be erased or inserted.

rp sq

p q sqr

rp sq

rp q

Page 18: Structured Knowledge

18

Existential GraphsProve: ((p r) (q s)) ((p q) (r s))

Erasure: in a positive context, any graph may be erased.

Insertion: in a negative context, any graph may be inserted.

Iteration: a copy of a graph may be written in the same context or any nested context.

Deiteration: any graph may be erased if a copy of its occurs in the same context or a containing context.

Double negation: two negations with nothing between them may be erased or inserted.

rp sq

p q sqr

rp sq

p q

r s

Page 19: Structured Knowledge

19

Existential GraphsProve: ((p r) (q s)) ((p q) (r s))

rp sq rp sq

rp

rp sq

rp q

rp sq

p q sqr

rp sq

p q

r s

Page 20: Structured Knowledge

20

Existential Graphs

• -graphs: propositional logic

• -graphs: first-order logic

• -graphs: high-order and modal logic

Page 21: Structured Knowledge

21

Semantic Nets

• Since the late 1950s dozens of different versions of semantic networks have been proposed, with various terminologies and notations.

• The main ideas:

For representing knowledge in structures

The meaning of a concept comes from the ways it is connected to other concepts

Labelled nodes representing concepts are connected by labelled arcs representing relations

Page 22: Structured Knowledge

22

Semantic Nets

Mammal

Person

Owen

Nose

Red Liverpool

isa

instance

has-part

uniform color tea

m

person(Owen) instance(Owen, Person)

team(Owen, Liverpool)

Page 23: Structured Knowledge

23

Semantic Nets

John

H1 H2

height

Bill

height

greater-than

1.80

value

Page 24: Structured Knowledge

24

Semantic Nets

John g

Give

agent

Book

b

instance instanceobjec

t

“John gives Mary a book”

Mary

beneficiarygive(John, Mary, book)

Page 25: Structured Knowledge

25

Frames

• A vague paradigm - to organize knowledge in high-level structures

• “A Framework for Representing Knowledge” - Minsky, 1974

• Knowledge is encoded in packets, called frames (single frames in a film)

Frame name + slots

Page 26: Structured Knowledge

26

FramesAnimals

AliveFlies

TF

Birds

LegsFlies

2T

Mammals

Legs 4

Penguins

Flies F

Cats Bats

LegsFlies

2T

Opus

NameFriend

Opus

Bill

NameFriend

Bill

Pat

Name Pat

instance

isa

isa

Page 27: Structured Knowledge

27

Frames

Hybrid systems:

Frame component: to define terminologies (predicates and terms)

Predicate calculus component: to describe individual objects and rules

Page 28: Structured Knowledge

28

Conceptual Graphs

• Sowa, J.F. 1984. Conceptual Structures: Information Processing in Mind and Machine.

• CG = a combination of Perice’s EGs and semantic networks.

Page 29: Structured Knowledge

29

Conceptual Graphs

• 1968: term paper to Marvin Minsky at Harvard.

• 1970's: seriously working on CGs

• 1976: first paper on CGs

• 1981-1982: meeting with Norman Foo, finding Peirce’s EGs

• 1984: the book coming out

• CG homepage: http://conceptualgraphs.org/

Page 30: Structured Knowledge

30

Simple Conceptual Graphs

CAT: tuna MAT: *On1 2

concept

relationconcept type (class)

relation type

individual referent

generic referent

Page 31: Structured Knowledge

31

Ontology

• Ontology: the study of "being" or existence

• An ontology = "A catalog of types of things that are assumed to exist in a domain of interest" (Sowa, 2000)

• An ontology = "The arrangement of kinds of things into types and categories with a well-defined structure" (Passin 2004)

Page 32: Structured Knowledge

32

Ontologytop-level categories

domain-specific

Page 33: Structured Knowledge

33

Ontology

Being

Substance Accident

Property Relation

Inherence Directedness

Movement IntermediacyQuantityQuality

Aristotle's categories

Containment

Activity Passivity Having Situated

Spatial Temporal

Page 34: Structured Knowledge

34

Ontology

Geographical-Feature

Area Line

On-Land On-Water

Road

Border

Mountain

Terrain

Block

Geographical categories

Railroad

Country

Wetland

Point

Power-Line

River

Heliport

Town

Dam

Bridge

Airstrip

Page 35: Structured Knowledge

35

Ontology

Relation

Page 36: Structured Knowledge

36

Ontology

Relation

Page 37: Structured Knowledge

37

Ontology

ANIMAL

FOOD

Eat

PERSON: john CAKE: *Eat

Page 38: Structured Knowledge

38

CG Projection

PERSON: john PERSON: *Has-Relative1 2

PERSON: john WOMAN: maryHas-Wife1 2

Page 39: Structured Knowledge

39

Nested Conceptual Graphs

It is not true that cat Tuna is on a mat.

CAT: tuna MAT: *OnNeg

CAT: tuna MAT: *On

Page 40: Structured Knowledge

40

Nested Conceptual Graphs

Every cat is on a mat.

CAT: * MAT: *On

CAT: *

coreference link

Page 41: Structured Knowledge

41

Nested Conceptual Graphs

Julian could not fly to Mars.

PERSON: julian PLANET: marsFly-To

Poss

Past

Page 42: Structured Knowledge

42

Nested Conceptual Graphs

Tom believes that Mary wants to marry a sailor.

PERSON: julian PLANET: marsFly-To

Poss

Past

Page 43: Structured Knowledge

43

Exercises

• Reading:

Sowa, J.F. 2000. Knowledge Representation: Logical, Philosophical, and Computational Foundations (Section 1.1: history of logic).

Way, E.C. 1994. Conceptual Graphs – Past, Present, and Future. Procs. of ICCS'94.