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Rep0 r t N u m b e r

DWIS.NASA/RECON-lO

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The USL/DEEUIS NASA/RECON Working Paper Series contains a collection of reports representing r e s u l t s of activities being conducted by the Computer Science Department of the University of Southwestern Louisiana pursuant to the specifications of National Aeronautics and Space Administration Contract Number NASW-3846. The work on this contract is being performed jointly by the University of Southwestern Louisiana and Southern University.

For more information, contact:

Wayne D. Dominick

Editor USL/DWIS NASA/REWWorking Paper Series

Computer Science Department University of Southwestern Louisiana

P. 0. Box 44330 Lafayette, Louisiana 70504

(318) 231-6308

. . . . . . . . . . . . . . . . . . . . . . I DBMS.NASA/REW-lO I

https://ntrs.nasa.gov/search.jsp?R=19890005587 2020-04-26T20:20:33+00:00Z

K N W E D G E BASED SYSTEUS:

A CRITICAL SURVEY OF MAJOR COINCEPTS,

ISSUES AND TECHNIQUES:

VISUALS

Srinu Kavi

Center for Advanced Computer Studies University of Southwestern Louisiana

Lafayette, Louisiana 70504 P. 0. Box 44330

D e c e m b e r 11, 1984

K N a E D G E BASED S Y S T M :

ISSUES, AND TECHNIQUES A CRITICAL SURVEX OF MAJOR CONCEPTS,

SRINU KAVI FALL 1984

.

OBJECTIVES

- To examine various issues and concepts involved in KBSs involved in KBSs

- To examine various techniques used to build KBSs

- To examine (at least one) KBS in detail ( L e o 9 case study)

- To list and identify limitations and problems w i t h KBSs

- To suggest future areas of research

- T o p r o v i d e e x t e n s i v e r e f e r e n c e s

TABLE OF CONTENTS

I . INTRODUCTION

2. KN-EDGE-BASED SYSTEMS (KBSS)

Introduction Hypothetical KBS KBS Components

3. TECHNIQUES USED TO CONSTRUCT KBSs

Introduction M e t h o d s of Representing Knowledge Inference Engine W o r k s p a c e Representation T h e Interface

4. KBS BUILDING TOOLS AND LANGUAGES

General Purpose P r o g r a m i n g Languages Skeletal Systems General Purpose Representation Languages Computer-Aided Design Tools Case Studies

'.

5. APPLICATION CONSID-TIONS

Initial Considerations Technology Considerations Environmental Considerations

6. CONCLUSIONS

7. POTENTIAL FUTURE RESEARCH AREAS

APPEND I C I ES

A. CASE STUDY - MYCIN B. LIST OF KBSs C. FIFTH GENERATION PROJECT

REFERENCES

'.

CHARACTERISTICS OF KBSs

- Organization of Knowledge

- Performance

- Utility ( o r Usefulness)

- Understandability ( o r Explainability)

- Heuristics

- Uncertainity

- Flexibility

- Modularity

TECHNIQUES USED TO CONSTRUCT KBSs

Introduction

Origins of KBS Techniques Choices and Restrictions Knowledge Representation Problems Knowledge Representation Forms Knowledge Representation Unit Credibility Factors Procedural Versus Declarative

Representation

M e t h o d s of Representing KB

Finite-State Machine Programs Predicate Calculus Production R u l e s Semantic Networks F r a m e s

Inference Engine (IE)

Primary Functions of IE Some Definitions IE Strategies M e t h o d s of Implementing the IE Measures of Performance

W o r k s p a c e Representation

Introduction HEARSAY-Blackboard AND/OR Gr a p h Blackboard Versus AND/OR Gr a p h

T h e Interface

Functions of the Interface User Interface Expert Interface Knowledge Acquisition (KA) Process

i

Table 3-1 ORIGINS OF KBS TECHNIQUES (Based on [Barnett & Bernstein, 7 7 1 )

ARTIFICIAL INTELLIGENCE (AI)

Heuristic Search Inference and Deduction Pattern Matching Knowledge Representation and

Acquisition S y s t e m Organization

LANGUAGE PROCESSING

Parsing and Understanding Question and Response Generation Knowledge Representation and

Acquisition

THEDRY OF PROGRAMMING LANGUAGES

Formal Theory of Computational Power Control Structures D a t a Structures S y s t e m Organization Par s i ng

NgODELING A N D SIMULATION

Representation of Knowledge Control Structures Calculation of Approximations

DATA BASE MANAGEME"

Information Retrieval U p d a t i ng File Organization

SOFWARE ENGINEXRING

S y s t e m Organization Do cumen t a t i on Iterative System Development

APPLICATION AREAS

Domain-Specific Algorithms H u m a n Engineering

..

f I

MODEL I

EXPERT'S I KNauDGE

d

B m REPRESENTATICPJ ' J

, I , 0

I I

r * I ' w ,

EXPERT'S I

- mKsPAcE REPRESENTATION

b

REASONING 3 INFERENCE PRINCIPLES I ENGINE

c i

USER EXPECTATIONS

EXPLANATION I

I SYSTEM I 1

TMTBOOKS

--------.--e-

KNaWLEDGE REPRESENTATION METHODS

- Finite state machines

- Programs

- Predicate calculus

- Production rules

- Semantic networks I

- F r a m e s

Representation = Knowledge + Access [Newell, 821

PRODUCTION SYSTEM COMPONENTS

Three parts [Barr & Feigenbaum, 811:

- A R u l e Base: A collection of production rules.

- A W o r k s p a c e : A buffer like data structure.

- A n Interpreter: W h i c h controls the system activity.

INTEZtPFWTER TASKS

- Matching or Building a Conflict-Set

- Conflict-Resolution

- Action or Execution

CONFLICT RESOLUTION STRATEGIES

- Rule Order

- Rule Precedence

- Generality Order

- Data Order

- Regency Order

- Non-Deterministic

AN EXAMPLE

Automotive Repair Agency

T h e S y s t e m Contains

- Knowledge Base of production rules (Performance characteristics and Measurable attributes)

- A Database (Past problems, Repairs, and Service performed)

Rl IF fan belt tension is low THEN alternator output will be low [ . 5 ] l

and engine will overheat [ . 2 ] I

I

R2 IF alternator output is low THEN battery charge will be low [ . ' ? ' I I

R3 IF battery is low THEN car will be difficult to start [.5]

R4 IF automatic choke malfunctions OR automatic choke needs adjustment

THEN car will be difficult to start [ . 8 ]

R5 IF battery is out of warranty THEN battery charge m a y be low [ . 9 ]

Figure 3-9 PRODUCTION RULES FOR AUTOMDTIVE SYSTEMS KS

R6 IF coolant is lost OR coolant system pressure cannot be maintained

THEN engine w i l l overheat [ . 7 ]

R7 IF there is a high resistance short AND fuse is not blown

THEN battery charge will be low [ . 8 ]

R8 IF battery flui-d is low THEN battery will boil off fluid [.3]

R9 IF battery fluid is low THEN battery charge will be l o w [ . 4 ]

Figure 3-9. PRODUCTION RULES FOR AUTONDTIVE SYSTEMS KS (CONT'D)

OBSEXVATIONS AGENT D I FF I CULTY

Alternate Output Level Battery Charge Level Battery Fluid Level Choke Adjustment Choke Function Coolant Level Coolant S y s t e m Pressure Difficulty to Start Engine Temperature F a n Belt Tension F u s e Condition Short in Electric S y s t m Voltage Regulator Level W a r r a n t i e s

M e c h 4 M e c h 3 S r v R 2 M e c h 5 M e c h 5 S r v R 2 M e c h 5 c u s t I c u s t I M e c h 3 S r v R 2 M e c h 8 M e c h 4 Da t a B a s e 0

Fi g u r e 3-10. DATA GATHERING PROCEDURE FACT FILE

< CHOKE OUT DIFFICULT r To START OF ARlusTFEM

FUSES NOT f%=J

b v

I I ! I

F W I D Lcsrl

. _ ,-I SHORT HIGH 1

VOLTAGE REGULATOR

I I

I I

& HIGH ENGINE

AGENTS

MECH (5

MECH(5)

SRVR(2)

SRVR (2 1

MECH(4)

h I

BAlTERY BAm VOLTAGE

Low HIGH HIGH FLUID CHARGE REG, OUTPUT

b -

FIGURE 3-E, FRAGMENT OF GRAPH STRUCTURE

+

VIS IBI LIlY OF

- I ta I RECT 4 LIHITED

~ + INTERACTION - CHANNEL BEHAVIOR

RULES AS + EXPLANA- - PRIMITIVE * TIONS OF ACT IONS SOLLJT I ON

L *

+

MOWLARITY

OF BEHAVIOR i

1 > + + ' A

CUNFLIC r- RESOLUTION STRATEGY BILITY

-NS1- t7

- MODIFI- ABILITY

I

FORMAT MCH I NE READ- ABILITY

+

I

I

+

FIGC~RE 3-14, WCTFRISTICS OF PRODUCTION SYSTFMS

BASED ON cBARNEll& BERNSTEIN, '771

SEMANTIC N E m R K s

Semantic networks are used in

Psychological modeling of human memory

P r o g r a m i n g languages

Natural language understanding

Data base management systems

A SEMANTIC N E m R K ( o r NET) consists of nodes and links.

TEMP (WARM-BLOODED MAMMAL) I SA (DOG, MAMMAL) I SA ( CAT, MAMMAL 1

LOC (MARY 's, F IDO) LOC (F I REHOUSE, BOWSER) LOC (BOB'S, PUFF) COLOR(TAN,FIDO) COLOR(TAN,BOWSER) COLOR(BLACK, PUFF)

BETWEEN(MARY'S,FIREHOUSE,BOB'S)

I SA (F fDOI DOG) I SA (BOWSER, DOG) I SA (PUFF, CAT)

S I Z E ( 4 0 L B , F I D O ) SIZE(14LB,BOWSER) S IZE(gLB,PUFF)

MAMMAL

P U W 3 C K 1 - -

rDM-nl I nnncn TEMpY \ I S A

PUFF

\ DhWPCD FIDO

MARY'S ~ O L B TAN 1 4 ~ ~ FIREHOUSE 4 LB BLACK BOB'S

Fi r s t Ru 1 e

PUFF is a cat and CAT is a MAMMAL; therefore, PUFF is a MAMUAL.

Second Rule

SIZE(4,PUFF) & SIZE(14,BCMEER) & 4 < 14 = > SMALLER(PUFF, B m E R )

Third Rule

ISA(FID0, DOG) & ISA(DOG, MAlvlMAL) = > ISA(FID0, MAlvlMAL)

ISA(FID0, MAMMAL) & TEMP(WmBLOODED, MANMAL) = >

TEMP(FID0, W m B L O O D E D )

MEANINGLESS INF'EEENCE

ISA(DOG, MAMUAL) &i ISA(CAT, MAMMAL) - - > ISA(DOG, CAT)

I"ERITABLE(TEMP)

- W h a t does a node (object) really mean?

- Is there a unique w a y to represent an idea?

- H o w is the passage of time to be represented?

- H o w does one represent things that are not facts about the world but rather ideas or beliefs?

- W h a t are the rules about inheritance of properties in networks?

FRAMES

Frame Characteristics

- Description

- Instantiation

- Prediction or Expectation

- Justification

- Variation

- Correction

- Perturbation

- Transformation

I dog FRAME I SA m a m a 1 2 kind breed 3 color SUBSET.OF {tan brown black

w h i t e rust]

4 F R O M c o l o r Q F k i n d

5 leggedness O . . . &

7 state d u 1 t . OR 6 weight ' 0 , ~ ~ Q E ~

puppy i f age < I 8 age ' 0 , now birth- *

9 bi r thday date IO n ame string

11 END dog

Figure 3-16. EXAMPLE FRAME DEFINITIONS [Barnett & Bernstein, 7'71

I boxer FRAME ISA 2 color

3 size 4 tai 1 5 ears 6 temperment 7 COMPLA I NT S

8 END

breed OF dog ONELOF { t a n

40.. . 6 0 bobbed OR long

p l a y f u l IF weight > I00 THEN ASSUME (great dane) boxer

brown brindle)

bobbed OR f l o p p y

F i g u r e 3-16. EXAMPLE FRAME DEFINITIONS (CONT'D) [Barnett & Bernstein, 771

L W - LEVEL I WORMAT I ON

OBJECT - 654

color = tan ears = bobbed leggedness = 4

temperment = m e a n size = 40 - 45

TRIAL IDENTIFICATION

[OBJECT 654 ISA dog

kind boxer WITH [ c o l o r tan size 40 - 45 tail ASSUMED bobbed ears bobbed temperment EXCEPTIONAL

me a n ] color tan leggedness 4

state ASSUMED adult] weight 40 - 45

F i g u r e 3-17. INEXACT MATCH BY A FRAME SYSTEM [Barnett & Bernstein, 771

INFERENCE ENGINE CONTROL STRATEGIES

- Forward chaining

- Backward chaining

- Chain both ways

- Middle t e r m chaining

- Fixed directionality

- Variable directionality

- Hybrid strategy

- Breadth-first

- Depth-first

&t

3 2 N

/ \ J \ \ 1 7

rl 9 0 76 I4 22

F m CHAINING

A 5 2 7 9

St 5 3

10 / $1 5 3

- -33, / =. 26 40

2080 121

CHAIN BOTH WAYS

BREADTH-FIRST CONTROL STRATEGY

An Example: 8-Puzzle

+ - - - + - - - + - - - + a.

s3

FIGURE 3-22, DEPM-FIRST BACK CHAI NING

.

/ \

METHODS OF IMPLEMENTING THE IE

Search Methods

Simulation Methods

Pattern Matching

SEARCH SYSTEM COMPONENTS

F i v e m a j o r components

Select

Expand

E v a 1 ua t e

Prune

Termi na t e

EVALUATION FUNCTION

"The purpose of a n evaluation function is to provide a m e a n s for ranking those nodes (activities) that are candidates for expansion to determine w h i c h one is most likely to be on the best path to the g o a l " [Nilsson, '711.

A' - AN OPTIMAL SEARCH ALGORITHM

In A * , the evaluation function, f'(x) is the cost of a solution path constrained to go through node x ; f ' should be -.

m- I f'(n(i)) = E K(n(j), n(j+l)) l<=i<=m

J = 1

f'(n) = f ' ( s t a r t , n ) + f'(n, goal)

f'(n) = g(n) + h(n)

f(n) = g ' ( n ) + h ' ( n ) .

MEASURES OF PERFORMANCE

Search Techniques

Penetrance

P = LIT L length of the derived path

T total number of nodes f r o m initial to goal

Branching Factor

172

a,

T = l 5 L = 3 P = us B = 2

FIGURE 3-27, =LE MO VF GRAPH AND B W D TREE

WRKSPACE REPRESENTATION

- Plan

- Agenda

- History

- Solution S e t

WW METHODS

- HEARSAY Blackboard

- AND/OR Graph

HEARSAY BLACKBOARD

A data structure

- Hypotheses and support criteria stored

- Intermediary between KSs and IE

-LEVELS-

CONCEPTUAL

PHRASAL

LEXICAL

SYLLABIC

SURFACE PHONEMIC

PHONETIC

1.-

SECMEMAL

PARAFlETRIC

-KNOWLEDGE SOURCES-

SEMANTIC WORD HYPOTHESIZER

SYNTACTIC PARSER

SYNTACTIC WORD HYPOTHESIZER

IWNW HYPOTHESIZER

WORD CANDIDATE GENERATOR

P"OL0GICAL RULE APPLIW

PWNE-PHONWE W"IZER

PHONE SYNTHES I ZER

SEGMENT PHONE SYNCHRONIZER

PARAMETER SEGMENT SWROkIIZER

SEGMENTER CLASSIFIER

FIGURE 3-28, HFARSAY I I 1 Fvfl S OF RE-TIOU' wasoURCEs BASED ON mrw, ET AL, '801

USER INPUT

Parsing Strategies

- Backtracking Versus Parallel Processing

- T o p Down Versus B o t t o m U p Processing

- Choosing How to Expand or Combine

I

~

- Multiple Knowledge Sources ~

PARSING SYSTEMS

- Template matching

- Transition networks

- Semantic gramnar parsers

TEMPLATE MATCHING

E . g . Y ELIZA, SIR, STUDENT

$1 x(i) ( I W A R E } NOT $2

UlHAT IF x ( i ) WEEW $ ( 2 ) ?

"Today's temperature is not hot"

"What i f temperature w e r e hot?"

RECURSIVE TRANSITION NEWRKS

E . g . Y "The little boy in the swimsuit k i c k e d the red b a l l "

NP: T h e little boy in t h e swimsuit

PP: in the swimsuit

NP: t h e swimsuit

V e r b : kicked

NP: t h e red ball

S: PP

NP <VERB> NP

NP:

PP:

NP

FIGURE 3-32, A RECURSIVF TRANSITION NETWORK BASED ON [BARR 8 FEIGENBAUN, ‘811

AUGMENTED TRANSITION NEWRKS

ATN - - > RTN extended in three ways

Regi s t e r s

Tests

Actions

DIFFICULTIES IN EXPLANATIONS k

- 7

% r

Explanations

- Must be in terms of

Knowledge chunks P r o b l e m parameters Inference rules

- Must be translated to human understanding

METHODS OF PROVIDING EXPLANATIONS

- W o r k s p a c e Representation

- Using Knowledge Source(s)

- Re-solve the P r o b l e m

c L

I -

f w

8 z 0

DIFFICULTIES IN K A

Representational mismatch

Verbalization by the expert (Protocol study)

Limitations on current technology

K A bottleneck

KBS BUILDING TOOLS AND LANGUAGES

- General purpose programning languages I

- Skeletal systems

- General purpose representation languages

- Computer-aided design tools for KBSs I

C a s e S t u d i e s

- EMYCIN

- HEARSAY-I11

- AGE

INITIAL CONSIDERATIONS

Task suitability

Availability of expert

KA process

Agreement w i t h the domain theory

E x p e r t ' s model

E x p e r t ' s principles of reasoning

Intermediate levels of abstraction

General versus domain s p e c i f i c knowledge

End users

Unanticipated support

Cost versus benefits

TECHNOLOGY CONSIDERATIONS

Building the prototype system

Chunk size

Representation of knowledge

Inference engine

M e t a knowledge

Procedural knowledge

Addition of knowledge by the users

Extensibility

Knowledge representation tools

Design of tools

K N a E D G E REPRESENTATION TOOLS

Generality

Appropriateness

Accessibility

Explanation/Interaction

P r o b l e m characteristics versus T o o l features

DESIGN OF TOOLS FOR BUILDING KBSs

- Generality

- Completeness

- High-level representation language

- Explanation/interaction facilities

- D a t a representation

- Control structure

E N V I R 0 " T A L CONSIDERATIONS

- Interactive KBSs

Interactive development

Local operating environment

CONCLUSIONS

- W i d e spectrum of application areas

- Highly successful

- S o m e systems are being used routinely (DENDRAL, MYCIN, RI, PROSPECTOR)

- Not yet corrmonly understood ( F e w "data points")

- M a j o r motivations

Replication/Distribution expertise

Union of expertise

D o cumen t at i on

- Building ESs expensive and time-consuming ($1-2 m i l l i o n ; 5 person-years with tools)

- General level of accomplishment high

- Number of unresolved issues

- Difficulties and potential risk

- High expectations/misunderstandings

..

POTENTIAL FUTURE RESEARCH AREAS

Knowledge acquisition

Representation theory

Cornparision of techniques

KBS building tools

Explanation

Evaluation

Parallel processing

Learning f r o m e x p e r i e n c e

Management of knowledge

Abstraction and hierarchies

Technological innovations

U n i f o r m terminology

1 1. R e p o n No. 2. Government Accession No. 3. Recipient’s Catalog No.

/ ~ ~ f i s - 6 5. Report Date

/# -8LL 4. Title and Subtitle

USL/NGT-19-010-900:, KNOWLEDGE BASED SYSTEMS: A CRITICAL SURVEY OF MAJOR CONCEPTS, ISSUES, AND TECHNIQUES: VISUALS

~

7. Author(s) SRINU KAVI

9. Performing Organization Name and Address

University of Southwestern Louisiana The Center for Advanced Computer Studies P.O. Box 44330 Lafayette, LA 70504-4330

12. Sponsoring Agency Name and Address

8. Performing Organization Report No.

10. Work Unit No.

11. Contract or Grant No.

NGT-19-010-900 13. Type of Repon and Period Covered

FINAL; 07/01/85 - 12/31/87 14. Sponsoring Agency Code

15. Supplementary Notes

16. Abstract

This Working Paper Series entry represents a collection of presentation visuals associated with the companion report entitled “Knowledge Based Systems: A Critical Survey of Major Concepts, Issues, and Techniques”, USL/DBMS NASA/RECON Working Paper Series report number DBMS .NASA/RECO N-9.

17. Key Words (Suggested by Authods) 1

Knowledge-Based Systems, Informa- tion Storage and Retrieval Systems

This report represents one of the 72 attachment reports to the University of Southwestern Louisiana’s Final Report on NASA Grant NGT-19-01G900. Accordingly, appropriate care should be taken in using this report out of the context of the full Final Report.

18. Distribution Statement

19. Security Classif. (of this report) 20. Security Classif. (of this page) 21. NO. of Pages

Unclassified . Unclassified 6 4

22. Rice’