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Expert SystemTools

ProgrammingLanguages

Problem Oriented(FORTRAN,

PASCAL)

SymbolManipulation

(LISP, PROLOG)

Knowledge

EngineeringLanguages

Skeletal System

General PurposeSystem

System BuildingAids

Design Aids

(AGE)

KnowledgeAcquisition Aids

(TEIRESIAS)

Support Facilities

Types of tools available for Expert System

building.

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Programming Languages:

Used for Expert System applications and generally either

i) Problem-oriented languages, such as FORTRAN andPASCAL. Problem oriented languages are designed for

particular classes of problem.

FORTRAN has convenient features for performing

algebraic calculations.

ii) Symbol Manipulation languages, such as LISP and PROLOG.

LISP has mechanisms for manipulating symbols in the

form of list structures.

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Knowledge Engineering Languages:

A knowledge engineering language is a sophisticated tool fordeveloping expert systems, consisting of an expert system building

language integrated into an extensive support environment.

a) Skeletal System: A skeletal knowledge engineering language is

simply a stripped-down expert system. The domain specific

knowledge is removed from the expert system, leaving only theinference engine and support facilities.

PROSPECTOR stripped down to KAS, a skeletal system for

diagnosis and classification.

MYCIN to EMYCIN

Easy and Fast.

Lack of Generality and Flexibility.

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General Purpose System: A general purpose KE language can

handle many different problem areas and types.

It provides more control over data access and search

than skeletal system but may be more difficult to use.

Vary according to the generality and flexibility.

The Skeletal and General purpose system all fall under the

category of research system.

Knowledge Engineering Languages:

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System Building Aids:

Consist of programs that help acquire and represent thedomain expertsknowledge and programs that help design

the expert system under construction.

i) Design Aids: Helps in designing.Example: AGE

ii) Knowledge Acquisition Aids: Helps in knowledge

Acquisition.

Example: TEIRESIAS

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AGE: Helps the knowledge engineer design and build an Expert System.

First used in HEARSAY in mid 1970s , HEARSAY-III HANNIBAL interpret the enemy radio communication data. It

uses the information about location and signal characteristics of

the data to identify organizational units and their communications

order of battle.

Provides the user with a set of components which like building

blocks, can be assembled to form portions of an expert system.

Each component, a collection of INTERLISP functions, supports an

expert system framework such as forward chaining, backward

chaining, or a blackboard architecture. The term blackboard refers to a central database used by systems

with this architecture to co-ordinate and control the operation of

independent group of rules called knowledge sources.

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TEIRESIAS

This System Building aid helps transfer knowledge from a

domain expert to a knowledge base.

INTERLISP.

Used initially for database maintenance. The system acquires new rules about the problem

domain through an interaction that allows users to state

rules in a restricted subset of English.

The system analyses the rules, makes suggestionsregarding their completeness and consistency, and helps

the user debugging them.

Rule designing

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Support Facilities

Consist of tools for helping programming

debugging aids

Knowledge base editors

To enhance capabilities of a finished system. Extra software packages

Components

Debugging aids

I/O facilities

Explanation facilities

Knowledge base editors

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Knowledge Engineering Languages for building Expert Systems:

TOOL TYPE FEATURES IMPLEMENTATION

LANGUAGE

DEVELOPER

EMYCIN SKELETAL SYSTEM Rule Based

Backward chaining

Certainty Handling

Explanation

Acquisition

INTERLISP Stanford University

EXPERT SKELETAL SYSTEM

Rule Based Forward chaining

Certainty Handling

Explanation

Acquisition

Consistency

Checking

FORTRAN Rutgers University

OPS5 General-purpose

system

Rule Based

Forward chaining

Flexible Control

Flexible

Representation

FRANZ LISP Carnegie-Mellon

University

ROSIE General-purpose

system

Rule Based

Forward chaining

Procedure

Oriented

English-like syntax

INTERLISP The Rand

Corporation

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MYCIN EMYCIN

SUPPORT

FACILITIES

KNOWLEDGE

BASE

(Infection

disease

expertise)

INFERENCE

ENGINE

SUPPORT

FACILITIES

KNOWLEDGE

BASE

(Empty)

INFERENCE

ENGINE

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Application of EMYCIN

EMYCIN

Helps determine

strategies for solvingstructural analysis

problems

Predicts whether or

not cornfields willbe damaged by

black cutworms.

Helps characterize

underground rock

by interpreting oil-

well log data

Diagnoses lung diseases

by interpreting

laboratory respiratory

tests

Helps select Therapy

for hospital patients

with depression

SACON

PLANT/ cdp

LITHO PUFF

BLUE BOX

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EXPERT

Uses rule based knowledge representation.

Forward chaining

Built in explanation facility, knowledge acquisition facility.

Consistency checking works by storing a database of

representative cases with known conclusions and using it to

test expert system after knowledge engineer adds new rules.

findings- f(finding name, truth value)

Hypothesis- h(name, certainty value).

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EXPERT

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Application of OPS5

OPS5

Helps salesperson

select initial sets ofcomponents for

XCON to configure

Configures VAX -

11/780 computersystems

Provides real time

interactive control

over the IBM MVS

operating system

Helps diagnose and treat

problems related to

drilling fluids used in

drilling operations

Helps locate faulty

components in PDP

11/03 computers

XSEL

XCON

YES/MVS MUD

IDT

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Application of ROSIE

ROSIE

Helps Air force

targeteers developplans for attacking

enemy airfields

Determine case

worth and liabilityfor product liability

cases

Locates and

identifies oil and

chemical spills at

Oak Ridge Nat. Lab.

Performs construction

claims analysis for

differing site condition

claims.

Helps intelligent

analysts withbattlefield situation

assessment

TATR

LDS

SPILLS DSCAS

ADEPT

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