인공지능 : 개념 및 응용 artificial intelligence: concepts and applications 6. 전문가...

인공지능 : 개념 및 응용 Artificial Intelligence: Concepts and ApplicationsArtificial Intelligence: Concepts and Applications

6. 6. 전문가 시스템전문가 시스템

도용태 김일곤 김종완 박창현 공저

전문가 시스템전문가 시스템 (Expert Systems)(Expert Systems)

특정의 문제를 해결하기 위해 특정의 전문적인 지식을 특정의 문제를 해결하기 위해 특정의 전문적인 지식을 기반으로 실행되는 컴퓨터 시스템기반으로 실행되는 컴퓨터 시스템

특정 문제 영역에서 그 영역의 인간 전문가가 의사 특정 문제 영역에서 그 영역의 인간 전문가가 의사 결정을 내리는 것과 유사하게 동작하는 컴퓨터 시스템결정을 내리는 것과 유사하게 동작하는 컴퓨터 시스템

인공지능 분야에서 상업적으로 성공한 대표적 분야인공지능 분야에서 상업적으로 성공한 대표적 분야

기능적 측면에서 필요한 요소기능적 측면에서 필요한 요소 추론 기능 사용자 - 시스템 간의 상호작용에 의한 데이터 획득 결론의 정당성 (Justification) 모듈 구조 (Modular architecture)




전문가 시스템의 배경전문가 시스템의 배경

문제해결을 위한 일반방법론을 찾고 , 범용 - 목적프로그램을 구축하고자 함

표현 및 탐색 기능을 향상시키는 일반 방법론을 찾고 , 특화된 프로그램을

구축하고자 함

매우 특화된 프로그램을 생성하기 위해 좁은

문제 영역에 대한 고수준의 정제된 지식을 이용

1960 1970 1980

high

low

PR

OG

RA

M

PO

WE

R




BreakthroughTo make a program intelligent, provide it with lots of high-

quality, specific knowledge about some problem areaBuilding Expert Systems

Knowledge Engineering: The process of building an expert system

Knowledge Engineer: Expert-system builderNeed the interaction between the KE and human experts

– The KE extracts procedures, strategies, and rules of thumb for problem solving

– The KE builds this knowledge into the expert systemResult: a program that solves problems like the human experts

DomainExpert

KnowledgeEngineer

Expert

System

Queries, Problems

Answers, Solutions

Strategies,Rules-of-thumb,

Domain rules




전문가 시스템 구축과정전문가 시스템 구축과정

KnowledgeEngineer

Expert

System

ExpertSystem

BuildingTool

End-User

DomainExpert

ClericalStaff

Toolbuilder

Builds Interviews

Extendsand tests

Builds,refines,

and tests Addsdata

UsesUses




Basic Components of Expert System (ES)Basic Components of Expert System (ES)

Experts/Knowledge EngineerExperts/Knowledge Engineer

Knowledge BaseKnowledge Base

Inference EngineInference Engine

User InterfaceUser Interface




Basic Concepts of Expert Systems - cont. Basic Concepts of Expert Systems - cont.

ExpertsExpertsRecognizing and formulating the problemSolving the problem quickly and properlyExplaining the solutionLearning from experienceRestructuring knowledgeDetermining relevance

Expertise is the extensive, task-specific knowledge Expertise is the extensive, task-specific knowledge acquired from training, reading and experienceacquired from training, reading and experience

Theories about the problem areaHard-and-fast rules and proceduresRules (heuristics)Global strategiesMeta-knowledge (knowledge about knowledge) Facts




Basic Concepts of Expert Systems - cont. Basic Concepts of Expert Systems - cont.

Transferring ExpertiseTransferring ExpertiseObjective of an expert system

To transfer expertise from an expert to a computer system and Then on to other humans (non-experts)

ActivitiesKnowledge acquisition Knowledge representation Knowledge inferenceKnowledge transfer to the user

Knowledge is stored in a knowledge baseTwo knowledge types

Fact / Procedures(rules)




The Knowledge EngineerThe Knowledge Engineer

Helps the expert(s) structure the problem area by Helps the expert(s) structure the problem area by interpreting and integrating human answers to questions, interpreting and integrating human answers to questions, drawing analogies, posing counterexamples, and drawing analogies, posing counterexamples, and bringing to light conceptual difficultiesbringing to light conceptual difficulties

Knowledge Acquisition SubsystemKnowledge Acquisition SubsystemKnowledge acquisition is the accumulation, transfer and

transformation of problem-solving expertise from experts and/or documented knowledge sources to a computer program for constructing or expanding the knowledge base

Usually also the System Usually also the System BuilderBuilder




The User The User

Possible Classes of Users Possible Classes of Users A non-expert client seeking direct advice - the ES acts as a

Consultant or AdvisorA student who wants to learn - an InstructorAn ES builder improving or increasing the knowledge base -

a PartnerAn expert - a Colleague or Assistant

The Expert and the Knowledge Engineer Should The Expert and the Knowledge Engineer Should Anticipate Users' Needs and Limitations When Anticipate Users' Needs and Limitations When Designing ES Designing ES




Knowledge BaseKnowledge Base

The knowledge base contains the knowledge necessary The knowledge base contains the knowledge necessary for understanding, formulating, and solving problemsfor understanding, formulating, and solving problems

Two Basic Knowledge Base ElementsTwo Basic Knowledge Base ElementsFactsSpecial heuristics, or rules that direct the use of knowledge Knowledge is the primary raw material of ESIncorporated knowledge representation




Inference EngineInference Engine

The brain of the ES The brain of the ES The control structure or the rule interpreterThe control structure or the rule interpreterProvides a methodology for reasoningProvides a methodology for reasoningThe computer is programmed so that it can make inferenThe computer is programmed so that it can make inferen

cesces

Major ElementMajor ElementInterpreterSchedulerConsistency Enforcer




User InterfaceUser Interface

Language processor for friendly, problem-oriented commLanguage processor for friendly, problem-oriented communication unication

NLP, or menus and graphicsNLP, or menus and graphics

Explanation subsystemExplanation subsystemTraces responsibility and explains the ES behavior by interactive

ly answering questions Why?

How?

What?

(Where? When? Who?)Knowledge Refining System

Learning for improving performance




Expert System Building ToolExpert System Building Tool(not the expert system)(not the expert system)

Expert System

Building Tool

Expert System

Building Language

Support

Environment

Expert

System

User




What Good Are Expert SystemsWhat Good Are Expert SystemsWhy not use real Experts?

→ Why do we develop expert systems

Comparing human and artificial expertise: the good news

The Good News

Human Expertise Artificial Expertise

Perishable Permanent

Difficult to transfer Easy to transfer

Difficult to document Easy to document

Unpredictable Consistent

Expensive Affordable




Why keep a human in the loop?

Why not eliminate human expert replacing them with expert systems?

Comparing human and artificial expertise: the bad news

The Bad News

Human Expertise Artificial Expertise

Creative Uninspired

Adaptive Needs to be told

Sensory experience Symbolic input

Broad focus Narrow focus

Commonsense knowledge Technical knowledge




How Are Expert Systems Organized?How Are Expert Systems Organized?Organizing Knowledge

Knowledge: The information a computer program needs with which it can behave intelligently

take the form of facts and rulessometimes considers uncertainty

Many of rules in expert systems are heuristicsComparing Algorithmic with Heuristic methods




The structure of an Expert SystemThe structure of an Expert System

Expert System

Knowledge Base(Domain Knowledge)

Facts

Rules

Interpreter

Scheduler

Inference Engine(General Problem-Solving

Knowledge)

KnowledgeRepresentations




Knowledge-Based SystemsKnowledge-Based Systems

ArtificialIntelligencePrograms

Knowledge-basedSystems

ExpertSystems

Exhibit intelligentbehavior by skillful

application of heuristics

Make domain knowledgeexplicit and separate from

the rest of the system

Apply expert knowledgeto difficult, real world

problems




How Do Expert Systems Differ from Conventional How Do Expert Systems Differ from Conventional ProgramsPrograms

Comparison of data processing and knowledge engineeringDate Processing Knowledge Engineering

Representations and use Representation and use of

of data knowledge

Algorithmic Heuristic

Repetitive Process Inferential process

Effective manipulation Effective manipulation of large

of large data bases knowledge bases




Basic Characteristics of an Expert SystemsBasic Characteristics of an Expert SystemsCharacteristics of an expert system that distinguish it from

a conventional program

Expert Systems sometimes make mistakes

Expertise

Symbolic reasoning

Depth

Self-Knowledge

Exhibit expert performanceHave high level of skillHave adequate robustness

Represent knowledge symbolically

Reformulate symbolic knowledge

Handle difficult problem domains

Use complex rules

Examine its own reasoning

Explain its operation

Expert SystemExpert System




What Have Expert Systems Been Used For?What Have Expert Systems Been Used For?Basic Activities of Expert Systems

Generic Categories

Category Problem Addressed

Interpretation Inferring situation descriptions from sensor data

Prediction Inferring likely consequences of given situations

Diagnosis Inferring system malfunctions from observables

Design Configuring objects under constraints

Planning Designing actions

Monitoring Comparing observations to expected outcomes

Debugging Prescribing remedies for malfunctions

Repair Executing plans to administer prescribed remedies

Instruction Diagnosing, debugging, and repairing user

behavior

Control Governing overall system behavior




Application Areas for Expert systemsChemistry

– DENDRAL, MOLGENComputer Systems

– XCONElectronics

– ACE, EURISKO, SOPHIEGeology

– PROSPECTORMedicine

– MYCIN, ONCOCIN, GUIDONMilitaryEngineering

인공지능 : 개념 및 응용 artificial intelligence: concepts and applications 6. 전문가...

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