Post on 12-Sep-2021
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.1
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c h a p t e r
1212121212121212MANAGING MANAGING
KNOWLEDGE: KNOWLEDGE:
KNOWLEDGE WORK KNOWLEDGE WORK
AND ARTIFICIAL AND ARTIFICIAL
INTELLIGENCEINTELLIGENCE
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LEARNING OBJECTIVES LEARNING OBJECTIVES 11//22
•• EXPLAIN ORGANIZATIONAL EXPLAIN ORGANIZATIONAL KNOWLEDGE MANAGEMENT KNOWLEDGE MANAGEMENT (Data/Knowledge)(Data/Knowledge)
•• DESCRIBE USEFUL APPLICATIONS FOR DESCRIBE USEFUL APPLICATIONS FOR DISTRIBUTING, CREATING, SHARING DISTRIBUTING, CREATING, SHARING KNOWLEDGEKNOWLEDGE
•• EVALUATE ROLE OF ARTIFICIAL EVALUATE ROLE OF ARTIFICIAL INTELLIGENCE IN INTELLIGENCE IN
KNOWLEDGE KNOWLEDGE MANAGEMENTMANAGEMENT
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AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.2
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LEARNING OBJECTIVES LEARNING OBJECTIVES 22//22
•• DEMONSTRATE HOW ORGANIZATIONS DEMONSTRATE HOW ORGANIZATIONS USE EXPERT SYSTEMS, CASEUSE EXPERT SYSTEMS, CASE--BASED BASED REASONING TO CAPTURE KNOWLEDGEREASONING TO CAPTURE KNOWLEDGE
•• DEMONSTRATE HOW NEURAL DEMONSTRATE HOW NEURAL NETWORKS & OTHER TECHNIQUES NETWORKS & OTHER TECHNIQUES IMPROVE KNOWLEDGE BASEIMPROVE KNOWLEDGE BASE
**
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MANAGEMENT CHALLENGESMANAGEMENT CHALLENGES
•• KNOWLEDGE MANAGEMENT IN THE KNOWLEDGE MANAGEMENT IN THE ORGANIZATIONORGANIZATION
•• INFORMATION & KNOWLEDGE INFORMATION & KNOWLEDGE WORK SYSTEMSWORK SYSTEMS
•• ARTIFICIAL INTELLIGENCE (AI)ARTIFICIAL INTELLIGENCE (AI)
•• OTHER INTELLIGENT TECHNIQUESOTHER INTELLIGENT TECHNIQUES
**
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.3
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KNOWLEDGE MANAGEMENT IN THE KNOWLEDGE MANAGEMENT IN THE
ORGANIZATION ORGANIZATION 11//33
KNOWLEDGE MANAGEMENT:KNOWLEDGE MANAGEMENT:Systematically & actively managing Systematically & actively managing and leveraging stores of knowledge and leveraging stores of knowledge in an organizationin an organization
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KNOWLEDGE MANAGEMENT IN THE KNOWLEDGE MANAGEMENT IN THE
ORGANIZATION ORGANIZATION 22//33
KNOWLEDGE MANAGEMENT:KNOWLEDGE MANAGEMENT:
Organizational learning mechanismsOrganizational learning mechanisms
Processes to create, gather, store, Processes to create, gather, store, maintain, disseminate knowledgemaintain, disseminate knowledge
CHIEF KNOWLEDGE OFFICERCHIEF KNOWLEDGE OFFICER (CKO)(CKO)
DIGITAL FIRM:DIGITAL FIRM: Substantial use of info Substantial use of info technology enhances ability to sense, technology enhances ability to sense, respond to environmentrespond to environment
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AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.4
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KNOWLEDGE MANAGEMENT IN THE KNOWLEDGE MANAGEMENT IN THE
ORGANIZATION ORGANIZATION 33//33
KNOWLEDGE MANAGEMENT:KNOWLEDGE MANAGEMENT:
Office Automation Systems Office Automation Systems (OAS)(OAS)
Knowledge Work Systems Knowledge Work Systems (KWS)(KWS)
Group Collaboration Systems Group Collaboration Systems (GCS)(GCS)
Artificial Intelligence Applications Artificial Intelligence Applications (AI)(AI)
**
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INFORMATION AND KNOWLEDGE INFORMATION AND KNOWLEDGE
WORK SYSTEMSWORK SYSTEMS
INFORMATION WORK:INFORMATION WORK: Work consists Work consists primarily of creating, processing primarily of creating, processing informationinformation
�� DATA WORKERS:DATA WORKERS: People who process &People who process &
disseminate organization’s ‘paperwork’disseminate organization’s ‘paperwork’
�������� KNOWLEDGE WORKERS:KNOWLEDGE WORKERS: People who:People who:
�������� DDesign products or services oresign products or services or
�������� CCreate new knowledge for organizationreate new knowledge for organization
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AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.5
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KNOWLEDGE MANAGEMENT & KNOWLEDGE MANAGEMENT &
INFORMATION TECHNOLOGYINFORMATION TECHNOLOGY
SHARE SHARE KNOWLEDGEKNOWLEDGE
DISTRIBUTE DISTRIBUTE KNOWLEDGEKNOWLEDGE
CREATE CREATE KNOWLEDGEKNOWLEDGE
CAPTURE, CAPTURE, CODIFY CODIFY KNOWLEDGEKNOWLEDGE
GROUP GROUP COLLABORATION COLLABORATION
SYSTEMSSYSTEMS
OFFICE OFFICE AUTOMATION AUTOMATION
SYSTEMSSYSTEMS
ARTIFICIAL ARTIFICIAL INTELLIGENCE INTELLIGENCE
SYSTEMSSYSTEMS
KNOWLEDGE KNOWLEDGE WORK WORK
SYSTEMSSYSTEMS
NETWORKSNETWORKS
DATABASESDATABASES
PROCESSORSPROCESSORS
SOFTWARESOFTWARE
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MAJOR ROLES OF OFFICESMAJOR ROLES OF OFFICES
(Office Activities)(Office Activities)
•• CoordinateCoordinate work of local work of local professionals and information professionals and information workersworkers
•• Coordinate work across levels and Coordinate work across levels and functionsfunctions
•• Couple organization to external Couple organization to external environment and operators (vendors, environment and operators (vendors, customers)customers)
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AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.6
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OFFICE AUTOMATION SYSTEMS OFFICE AUTOMATION SYSTEMS 11//55
MANAGING DOCUMENTS:MANAGING DOCUMENTS:
•• CREATIONCREATION
•• STORAGESTORAGE
•• RETRIEVALRETRIEVAL
•• DISSEMINATIONDISSEMINATION
•• TECHNOLOGY:TECHNOLOGY: Word processing, desktop Word processing, desktop publishing, document imaging, Web publishing, document imaging, Web publishing, work flow managerspublishing, work flow managers
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OFFICE AUTOMATION SYSTEMS OFFICE AUTOMATION SYSTEMS 22//55SCHEDULING:SCHEDULING:
For individuals & groups:For individuals & groups:
•• Electronic Calendars (Desktop/Web)Electronic Calendars (Desktop/Web)
•• GroupwareGroupware
•• IntranetsIntranets
•• Events planning SWEvents planning SW
•• ToTo--Do listsDo lists
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AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.7
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OFFICE AUTOMATION SYSTEMS OFFICE AUTOMATION SYSTEMS 33//55COMMUNICATING:COMMUNICATING:
INITIATING, RECEIVING, MANAGING:INITIATING, RECEIVING, MANAGING:
•• VOICEVOICE
•• DIGITALDIGITAL
•• DOCUMENTSDOCUMENTS
•• TECHNOLOGY:TECHNOLOGY: EE--mail, voice mail, digital mail, voice mail, digital answering systems, GroupWare, intranets, answering systems, GroupWare, intranets, contact management systems, Web contact management systems, Web 22..0 0 applicationsapplications
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OFFICE AUTOMATION SYSTEMS OFFICE AUTOMATION SYSTEMS 44//55MANAGING DATA (a):MANAGING DATA (a):
Employees, customers, vendors:Employees, customers, vendors:
•• Desktop databasesDesktop databases
•• SpreadsheetsSpreadsheets
•• UserUser--friendly interfaces to mainframe friendly interfaces to mainframe databasesdatabases
•• Cloud/nonCloud/non--cloud based HR Systemscloud based HR Systems
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AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.8
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•• DOCUMENT IMAGING SYSTEMS:DOCUMENT IMAGING SYSTEMS: Systems Systems convert documents, images into digital form (e.g.: convert documents, images into digital form (e.g.: optical character recognition; microfiche)optical character recognition; microfiche)
•• OCR SystemsOCR Systems
•• JUKEBOX:JUKEBOX: Storage & retrieving device for CDStorage & retrieving device for CD--ROMs & other optical disksROMs & other optical disks
•• INDEX SERVER:INDEX SERVER: Imaging system to store / retrieve Imaging system to store / retrieve documentdocument
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OFFICE AUTOMATION SYSTEMS OFFICE AUTOMATION SYSTEMS 55//55MANAGING DATA (b):MANAGING DATA (b):
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CREATE KNOWLEDGE CREATE KNOWLEDGE 11//44KNOWLEDGE WORK SYSTEMS:KNOWLEDGE WORK SYSTEMS:
Information systems that aid Information systems that aid knowledge workers to:knowledge workers to:
�������� CreateCreate
�� IntegrateIntegrate
New knowledge in organizationNew knowledge in organization
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AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.9
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CREATE KNOWLEDGE CREATE KNOWLEDGE 22//44KNOWLEDGE WORKERS:KNOWLEDGE WORKERS:
•• KEEP ORGANIZATION UPKEEP ORGANIZATION UP--TOTO--DATE IN DATE IN KNOWLEDGE:KNOWLEDGE: Technology; science; Technology; science; thought; the artsthought; the arts
•• INTERNAL CONSULTANTS ININTERNAL CONSULTANTS INTHEIR AREASTHEIR AREAS
•• CHANGE AGENTS:CHANGE AGENTS: Evaluating; Evaluating; initiating; promoting changeinitiating; promoting changeprojectsprojects
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•• CAD/CAM: CAD/CAM: Computer Aided Computer Aided Design/Computer Aided Design/Computer Aided
Manufacturing: Provides Manufacturing: Provides precise control over industrial precise control over industrial design, manufacturingdesign, manufacturing
•• VIRTUAL REALITY:VIRTUAL REALITY: Interactive Interactive softwaresoftware creates photorealistic creates photorealistic
simulations of real world objects simulations of real world objects (Virtual Reality Modeling (Virtual Reality Modeling Language: Language: VRMLVRML))
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CREATE KNOWLEDGE CREATE KNOWLEDGE 33//44KNOWLEDGE SYSTEMS:KNOWLEDGE SYSTEMS:
AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.10
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•• INVESTMENT WORKSTATIONS:INVESTMENT WORKSTATIONS:HighHigh--end PCs used in finance end PCs used in finance to analyze trading situations, to analyze trading situations, facilitate portfolio managementfacilitate portfolio management
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CREATE KNOWLEDGE CREATE KNOWLEDGE 44//4 4 KNOWLEDGE SYSTEMS:KNOWLEDGE SYSTEMS:
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SHARE KNOWLEDGESHARE KNOWLEDGEGROUP COLLABORATION SYSTEMS:GROUP COLLABORATION SYSTEMS:
•• GROUPWARE:GROUPWARE: Allows interactive Allows interactive concurrent collaboration, approval of concurrent collaboration, approval of documents, and so ondocuments, and so on
•• INTRANETS/Web:INTRANETS/Web: Good for relatively Good for relatively stable information in central repositorystable information in central repository
•• TEAMWARE:TEAMWARE: Group collaborative software Group collaborative software to customize team effortsto customize team efforts
•• Web/WikisWeb/Wikis..
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AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.11
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CAPABILITIES OF GROUPWARECAPABILITIES OF GROUPWARE
•• Publishing, ReplicationPublishing, Replication
•• Discussion Tracking (Legal Discussion Tracking (Legal Documentation) Documentation) �������� RecordRecord
•• Document ManagementDocument Management
•• WorkWork--flow Managementflow Management
•• Portability (Formats/Web/Integration)Portability (Formats/Web/Integration)
•• SecuritySecurity
•• Application DevelopmentApplication Development
**
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ARTIFICIAL INTELLIGENCE ARTIFICIAL INTELLIGENCE
(AI) SYSTEMS:(AI) SYSTEMS:
AI:AI: COMPUTERCOMPUTER--BASED SYSTEMS WITH BASED SYSTEMS WITH ABILITIES TO ABILITIES TO LEARN LANGUAGELEARN LANGUAGE, , ACCOMPLISH TASKSACCOMPLISH TASKS, , USE PERCEPTUAL USE PERCEPTUAL APPARATUS (APPARATUS (إدراك صناعيإدراك صناعي)), , EMULATE EMULATE HUMAN EXPERTISEHUMAN EXPERTISE & & DECISION MAKINGDECISION MAKING
**
AI
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AI FAMILYAI FAMILYAI FAMILYAI FAMILYAI FAMILYAI FAMILYAI FAMILYAI FAMILY
NATURALNATURAL
LANGUAGELANGUAGEROBOTICSROBOTICS
PERCEPTIVEPERCEPTIVE
SYSTEMSSYSTEMS
EXPERTEXPERT
SYSTEMSSYSTEMS
INTELLIGENTINTELLIGENT
MACHINESMACHINES
ARTIFICIALARTIFICIAL
INTELLIGENCEINTELLIGENCE
AI
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AI BUSINESS INTERESTS BUSINESS INTERESTS
IN AI IN AI
•• PRESERVE EXPERTISEPRESERVE EXPERTISE
•• CREATE KNOWLEDGE BASECREATE KNOWLEDGE BASE
•• MECHANISM NOT SUBJECT TO FEELINGS, MECHANISM NOT SUBJECT TO FEELINGS, FATIGUE, WORRY, CRISISFATIGUE, WORRY, CRISIS
•• ELIMINATE ROUTINE / UNSATISFYING JOBSELIMINATE ROUTINE / UNSATISFYING JOBS
•• ENHANCE KNOWLEDGE BASE (Continuous ENHANCE KNOWLEDGE BASE (Continuous Evolution)Evolution)
•• Machine vs. HumanMachine vs. Human
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AI EXPERT SYSTEMS EXPERT SYSTEMS 11//55
An expert system is subfield of AI, that An expert system is subfield of AI, that attempts to provide an answer to a attempts to provide an answer to a problem, or clarify uncertainties where problem, or clarify uncertainties where normally one or more human experts would normally one or more human experts would need to be consulted, usually in a specific need to be consulted, usually in a specific problem domain.problem domain.
So..So..
KNOWLEDGE KNOWLEDGE -- INTENSIVE CAPTURES INTENSIVE CAPTURES HUMAN EXPERTISE IN LIMITED DOMAINS HUMAN EXPERTISE IN LIMITED DOMAINS
OF KNOWLEDGE (EXPERTISE)OF KNOWLEDGE (EXPERTISE)
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EXPERT SYSTEMS EXPERT SYSTEMS 22//55
•• KNOWLEDGE BASE:KNOWLEDGE BASE: Model of Human Model of Human KnowledgeKnowledge
•• RULERULE--BASED EXPERT SYSTEM :BASED EXPERT SYSTEM : AI AI system based on IF system based on IF -- THEN statements THEN statements (Bifurcation (Bifurcation تشعباتتشعبات); Rule Base: Collection ); Rule Base: Collection of IF of IF -- THEN knowledgeTHEN knowledge
•• KNOWLEDGE FRAMESKNOWLEDGE FRAMES: Knowledge : Knowledge organizes in chunks based on shared organizes in chunks based on shared relationshipsrelationships
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AI
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EXPERT SYSTEMS EXPERT SYSTEMS 33//55
•• AI SHELL:AI SHELL: Programming environment of Programming environment of expert systemexpert system
•• INFERENCE ENGINE:INFERENCE ENGINE: Search through rule Search through rule basebase
–– FORWARD CHAINING:FORWARD CHAINING: Uses input; searches rules for answer
–– BACKWARD CHAINING:BACKWARD CHAINING: Begins with hypothesis, seeks information until hypothesis accepted or rejected
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AI
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EXPERT SYSTEMS EXPERT SYSTEMS 44//55EXAMPLES:EXAMPLES:
•• BLUE CROSS BLUE SHIELD:BLUE CROSS BLUE SHIELD:Automated medical underwriting Automated medical underwriting systemsystem
•• COUNTRYWIDE FUNDING CORP.:COUNTRYWIDE FUNDING CORP.:Loan underwriting expert systemLoan underwriting expert system
•• UNITED NATIONS:UNITED NATIONS: Employee salary Employee salary calculationscalculations
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AI
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EXPERT SYSTEMS EXPERT SYSTEMS 55//5 5 LIMITATIONS:LIMITATIONS:
•• Often reduced to problems of Often reduced to problems of classification for different casesclassification for different cases
•• Can be large, lengthy, expensive to Can be large, lengthy, expensive to implementimplement
•• Maintaining knowledge base criticalMaintaining knowledge base critical
•• Many managers unwilling to trust such Many managers unwilling to trust such systems (in DSS)systems (in DSS)
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AI
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AICASECASE--BASED REASON (CBR)BASED REASON (CBR)
CBR:CBR: Process of solving new Process of solving new problems based on the problems based on the sol’nssol’ns ofofsimilar past problems.similar past problems.
4 4 Steps:Steps: Retrieve, Reuse, Revise, RetainRetrieve, Reuse, Revise, Retain
AI uses database of cases:AI uses database of cases:
•• User describes problemUser describes problem
•• System searches database for similar casesSystem searches database for similar cases
•• System asks more questionsSystem asks more questions
•• Finds closest fitFinds closest fit
•• Modified as requiredModified as required
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AQU – Information Systems Fundamentals – Spring 2012. Pg. 12.16
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•• NEURAL NETWORKS: Software attempts to NEURAL NETWORKS: Software attempts to emulate brain processesemulate brain processes
•• FUZZY LOGIC: Tolerates ambiguity using FUZZY LOGIC: Tolerates ambiguity using nonspecific MEMBERSHIP FUNCTIONSnonspecific MEMBERSHIP FUNCTIONS
•• GENETIC ALGORITHMSGENETIC ALGORITHMS
•• INTELLIGENT AGENTSINTELLIGENT AGENTS
•• HYBRID AI SYSTEMS: CombinationsHYBRID AI SYSTEMS: Combinations
**
AI OTHER APPROACHESOTHER APPROACHES
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NEURAL NETWORKS (ANN)NEURAL NETWORKS (ANN)•• Mathematical/computational model that tries to Mathematical/computational model that tries to
simulate the structure and/or functional aspects of simulate the structure and/or functional aspects of biological neural networks.biological neural networks.
•• ANN consists of an interconnected group of artificial ANN consists of an interconnected group of artificial neurons, and it processes information using a neurons, and it processes information using a connectionist approach to computation.connectionist approach to computation.
•• Usually it’s adaptive system (changes its structure Usually it’s adaptive system (changes its structure based on external or internal information that flows based on external or internal information that flows through the network during the learning phase) through the network during the learning phase) ��������learn=usagelearn=usage
•• ANN are usually models complex relationships ANN are usually models complex relationships bet’nbet’nii//p’sp’s and o/and o/p’sp’s to find patterns in data.to find patterns in data.
•• App’nsApp’ns in real life: classifications, ein real life: classifications, e--learning, DSSlearning, DSS
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FUZZY LOGICFUZZY LOGIC
•• A form of manyA form of many--valued logic valued logic
•• To deal with reasoning that is fluid or To deal with reasoning that is fluid or approximate rather than preciseapproximate rather than precise
•• In contrast with "crisp logic“ In contrast with "crisp logic“ �������� 00//11
•• Fuzzy logic variables may have a truth Fuzzy logic variables may have a truth value that ranges in degree between value that ranges in degree between 0 0 and and 11
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GENETIC ALGORITHMSGENETIC ALGORITHMS
•• Search technique to find Search technique to find exactexact or or approximateapproximate solutions to optimization and solutions to optimization and search problems.search problems.
•• They are evolutionary algorithms (EA) that They are evolutionary algorithms (EA) that use techniques such as inheritance, use techniques such as inheritance, mutation, & selection, and crossover.mutation, & selection, and crossover.
•• Use models of organisms to promote Use models of organisms to promote evolution of solutionevolution of solution
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AI
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AI INTELLIGENT AGENT INTELLIGENT AGENT 11//22
•• Autonomous entity which observes Autonomous entity which observes and acts upon an environment (it’s and acts upon an environment (it’s agent) and directs its activity towards agent) and directs its activity towards achieving goals (it is rational).achieving goals (it is rational).
•• IA may also learn or use knowledge to IA may also learn or use knowledge to achieve their goals.achieve their goals.
•• The meaning is general (a human The meaning is general (a human being, a community of human beings being, a community of human beings working together towards a goal).working together towards a goal).
•• So in CS they are usually referred to So in CS they are usually referred to as Abstract IA’sas Abstract IA’s
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INTELLIGENT AGENT INTELLIGENT AGENT 22//22
Program with builtProgram with built--in, learned in, learned knowledge base to do specific, knowledge base to do specific, repetitive, predictable tasks for:repetitive, predictable tasks for:
•• IndividualIndividual
•• Business processBusiness process
•• Software applicationSoftware application
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AI
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DIKWDIKW Hierarchy / Wisdom Hierarchy / Hierarchy / Wisdom Hierarchy /
Knowledge Hierarchy / Information Knowledge Hierarchy / Information
Hierarchy / Knowledge PyramidHierarchy / Knowledge Pyramid
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c h a p t e r
1212121212121212MANAGING MANAGING
KNOWLEDGE: KNOWLEDGE:
KNOWLEDGE WORK KNOWLEDGE WORK
AND ARTIFICIAL AND ARTIFICIAL
INTELLIGENCEINTELLIGENCE