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Artificial Intelligence (AI)Artificial Intelligence (AI)
Dr. Merle P. MartinDr. Merle P. MartinMIS DepartmentMIS DepartmentCSU SacramentoCSU Sacramento
AcknowledgementsAcknowledgements Dr. Russell ChingDr. Russell Ching ( (MIS DeptMIS Dept) )
Source Materiel / GraphicsSource Materiel / Graphics Edie SchmidtEdie Schmidt ( (UMSUMS) - Graphic Design) - Graphic Design Prentice Hall PublishingPrentice Hall Publishing (Permissions) (Permissions)
Martin, Martin, Analysis and Design ofAnalysis and Design of Business Information SystemsBusiness Information Systems, 1995, 1995
AgendaAgenda Gate Assignment ProblemGate Assignment Problem Artificial IntelligenceArtificial Intelligence Expert Systems (Expert Systems (ES)ES) ES ExamplesES Examples
In the Airline IndustryIn the Airline Industry United Airlines' GADS United Airlines' GADS
(Gate Assignment Display (Gate Assignment Display System)System)
Trans World Airlines' GATES Trans World Airlines' GATES (Gate Assignment and Tracking (Gate Assignment and Tracking Expert System)Expert System)
Boeing 747, Boeing 747, 387-427 capacity387-427 capacity
Lockheed L-1011, Lockheed L-1011, 252 capacity252 capacity
Boeing 767, Boeing 767, 170-227 capacity170-227 capacity
Boeing 727, Boeing 727, 115-134 capacity115-134 capacity
Gate Assignment ProblemGate Assignment ProblemConstraints:Constraints: Matching size of aircraft to gate Matching size of aircraft to gate
8 different types with United 8 different types with United 6 with TWA 6 with TWA
Minimizing distances between Minimizing distances between connecting flightsconnecting flights
Foreign vs. domestic flightForeign vs. domestic flight
GATES ConstraintsGATES Constraints Constraints without exceptionsConstraints without exceptions
Gate sizeGate size Constraints with exceptionsConstraints with exceptions
International versus domestic International versus domestic flightsflights
Constraints with changing tolerancesConstraints with changing tolerances Turn-around timesTurn-around times
GuidelinesGuidelines Taxiway congestionTaxiway congestion
Convenience constraintsConvenience constraints Time between flightsTime between flights Distance between Distance between
connecting flightsconnecting flights
GATES Constraints GATES Constraints
ES benefits: ES benefits: Task of scheduling gate Task of scheduling gate
assignments for a month assignments for a month reduced from 15 hours reduced from 15 hours to 30 seconds.to 30 seconds.
ES can be transferred to other ES can be transferred to other airport operations, reducing airport operations, reducing training / operating costs.training / operating costs.
Gate Assignment Gate Assignment
Benefits (Cont.) Benefits (Cont.) Decrease susceptibility of Decrease susceptibility of
schedule to moods and schedule to moods and whims of schedulers. whims of schedulers.
Gate assignments can be done Gate assignments can be done on demand with little interference on demand with little interference to current operations. to current operations.
Gate Assignment Gate Assignment
Benefits (Cont.)Benefits (Cont.) Managers can review impact Managers can review impact
of changes, implement changes of changes, implement changes (i.e., what-if analysis).(i.e., what-if analysis).
ES integrated into airlines' ES integrated into airlines' major operations / scheduling major operations / scheduling systems through direct electronic systems through direct electronic interfaces, thus expediting interfaces, thus expediting scheduling.scheduling.
Gate Assignment Gate Assignment
Artificial Intelligence (Artificial Intelligence (AI)AI)Effort to develop Effort to develop
computer-based systemscomputer-based systems that behave like humans:that behave like humans:
learn languageslearn languages accomplish physical tasksaccomplish physical tasks use a perceptual apparatususe a perceptual apparatus emulate human thinkingemulate human thinking
AI BranchesAI Branches Natural LanguageNatural Language RoboticsRobotics Perceptive SystemsPerceptive Systems Expert SystemsExpert Systems Intelligent MachinesIntelligent Machines
Human Processing Human Processing CapabilitiesCapabilities Induction:Induction:
act on inconsistently act on inconsistently formatted dataformatted data
fill in the gapsfill in the gaps CN U RD THSCN U RD THS Wheel of FortuneWheel of Fortune
AdaptivenessAdaptiveness
Human Processing Human Processing CapabilitiesCapabilities Insight:Insight:
creativitycreativity create alternativescreate alternatives chess gamechess game perspicuous groupingperspicuous grouping
Perspicuous GroupingPerspicuous Grouping Recognize that we can Recognize that we can
handle only a few alternativeshandle only a few alternatives Short Term Memory (Short Term Memory (STMSTM)) Miller’s 7 +/- 2 RuleMiller’s 7 +/- 2 Rule
Zero in on a few viable alternativesZero in on a few viable alternatives Enumerate / select bestEnumerate / select best Satisficing, rather than optimizingSatisficing, rather than optimizing Herbert Simon’s 1958 Chess predictionHerbert Simon’s 1958 Chess prediction
Computer Processing Computer Processing CapabilitiesCapabilities Handle large volume of dataHandle large volume of data
quicklyquickly Detect signals Detect signals
where humans sense “where humans sense “noisenoise”” TirelessTireless
Computer CapabilitiesComputer Capabilities ConsistentConsistent ObjectiveObjective
no “no “selective perceptionselective perception”” Not distractedNot distracted Minimal “Minimal “down-time”down-time”
IssueIssueA Stanford Research Institute A Stanford Research Institute
(SRI) scientist once said, (SRI) scientist once said, “You needn’t fear intelligent “You needn’t fear intelligent machines. Maybe they’ll machines. Maybe they’ll keep us as pets.”keep us as pets.” Will intelligent machines Will intelligent machines
replace us?replace us? Why or why not?Why or why not?
WHAT DO YOU THINK?WHAT DO YOU THINK?
What is an ES?What is an ES? Feigenbaum, 1983Feigenbaum, 1983““intelligent intelligent computer programcomputer programusing knowledge / using knowledge / inference proceduresinference proceduresto solve problems difficult enoughto solve problems difficult enoughto require significant to require significant human expertisehuman expertise;;a a modelmodel of the expertise ofof the expertise ofthe best the best practitioners” practitioners”
Components of an Expert SystemComponents of an Expert SystemKnowledge Knowledge
BaseBase
Recom-Recom-mendedmendedActionAction
Inference Inference EngineEngine
User User InterfaceInterface
ExplanationExplanationFacilityFacility
Facts and RulesFacts and Rules
UserUser
KnowledgeKnowledgeAcquisitionAcquisition
FacilityFacility
Rule InductionRule Induction
Case Classified Through
Deduction
Rules Induced
From Example
Cases
Individual Cases
Applied to the Rules
InductionInduction(Inductive Logic)(Inductive Logic)
DeductionDeduction(Deductive Logic)(Deductive Logic)
Pay or Pay or Reject Reject Pay or Pay or Reject Reject
Type of Type of AccountAccountType of Type of AccountAccount
Credit Credit RatingRatingCredit Credit RatingRating
Overdraft Overdraft for Single for Single or Multiple or Multiple Checks Checks
Overdraft Overdraft for Single for Single or Multiple or Multiple Checks Checks
PayPayPayPay RegularRegularRegularRegular GoodGoodGoodGood MultipleMultipleMultipleMultiplePayPayPayPay StudentStudentStudentStudent UnknownUnknownUnknownUnknown SingleSingleSingleSingle
RejectRejectRejectReject StudentStudentStudentStudent PoorPoorPoorPoor SingleSingleSingleSingleRejectRejectRejectReject StudentStudentStudentStudent GoodGoodGoodGood MultipleMultipleMultipleMultiple
PayPayPayPay StudentStudentStudentStudent GoodGoodGoodGood SingleSingleSingleSingle
DecisionDecisionDecisionDecision Decision AttributesDecision AttributesDecision AttributesDecision Attributes
Check Overdraft CasesCheck Overdraft Cases
Pay or Pay or Reject Reject Pay or Pay or Reject Reject
Type of Type of AccountAccountType of Type of AccountAccount
Credit Credit RatingRatingCredit Credit RatingRating
Overdraft Overdraft for Single for Single or Multiple or Multiple Checks Checks
Overdraft Overdraft for Single for Single or Multiple or Multiple Checks Checks
DecisionDecisionDecisionDecision Decision AttributesDecision AttributesDecision AttributesDecision Attributes
PayPayPayPay RegularRegularRegularRegular UnknownUnknownUnknownUnknown MultipleMultipleMultipleMultiplePayPayPayPay RegularRegularRegularRegular GoodGoodGoodGood SingleSingleSingleSingle
RejectRejectRejectReject RegularRegularRegularRegular PoorPoorPoorPoor SingleSingleSingleSingleRejectRejectRejectReject StudentStudentStudentStudent UnknownUnknownUnknownUnknown MultipleMultipleMultipleMultipleRejectRejectRejectReject RegularRegularRegularRegular UnknownUnknownUnknownUnknown MultipleMultipleMultipleMultiple
Check Overdraft Cases Check Overdraft Cases (Cont.)(Cont.)
Pay or Pay or Reject Reject Pay or Pay or Reject Reject
Type of Type of AccountAccountType of Type of AccountAccount
Credit Credit RatingRatingCredit Credit RatingRating
Overdraft Overdraft for Single for Single or Multiple or Multiple
Checks Checks
Overdraft Overdraft for Single for Single or Multiple or Multiple
Checks Checks
???? RegularRegularRegularRegular UnknownUnknownUnknownUnknown SingleSingleSingleSingle
Pay or Reject?Pay or Reject?
Bank Overdraft Bank Overdraft ApplicationApplication 340 Cases of check 340 Cases of check
overdraftsoverdrafts Classification Variable:Classification Variable:
Check unpaid(0) or paid (1)Check unpaid(0) or paid (1)
ID3 DECISION TREEID3 DECISION TREE176130
1165
60125
5957
501
21
01
20
480
956
556
40
354
22
21
01
168
053
115
10
015
154
142
12
1011
690
321
320
01
Pay Reject Pay
Reject Pay
Reject Reject Reject Pay Reject Pay
Pay Reject Pay Reject
DIFF<20.5
DIFF<10.5
DIFF<9.4DIFF<40.3
DIFF<42.2
CR *DIFF<6.5
CR *DIFF<.035
DIFF<1.65
ACT*DIFF<.175
CR*DIFF<5.5
COV*DIFF<1.5
DIFF<5.55
ACT*DIFF<3
Yes No
Yes No Yes No
ACT*DIFF<19.6
Overall Classification Overall Classification Rate: 97.7%Rate: 97.7%
Reasons For Using ESReasons For Using ES ConsistentConsistent Never gets bored / overwhelmedNever gets bored / overwhelmed Replace absent, scarce expertsReplace absent, scarce experts Quick response timeQuick response time
ES ReasonsES Reasons Reduced down-timeReduced down-time Cheaper than expertsCheaper than experts Integration of multi-expert opinionsIntegration of multi-expert opinions Eliminate routine / unsatisfactory Eliminate routine / unsatisfactory
jobs for peoplejobs for people
ES LimitationsES Limitations High development costHigh development cost Limited to relatively simple Limited to relatively simple
problemsproblems operational mgmt leveloperational mgmt level
Can be difficult to useCan be difficult to use Can be difficult to maintainCan be difficult to maintain
When to Use ESWhen to Use ES High potential payoffHigh potential payoff OROR Reduced riskReduced risk Need to replace expertsNeed to replace experts
Campbell’s SoupCampbell’s Soup
When to Use ESWhen to Use ES Need more consistency Need more consistency
than humansthan humans Expertise needed Expertise needed
at various locations at various locations at same timeat same time
Hostile environment Hostile environment dangerous to human healthdangerous to human health
ES Versus DSSES Versus DSS Problem Structure:Problem Structure:
ES: structured problemsES: structured problems clearclear consistentconsistent unambiguousunambiguous
DSS: semi-structured problemsDSS: semi-structured problems
ES Versus DSSES Versus DSS Quantification:Quantification:
DSS: quantitativeDSS: quantitative ES: non-mathematical ES: non-mathematical
reasoningreasoningIF A BUT NOT B, THEN ZIF A BUT NOT B, THEN Z
Purpose:Purpose: DSS: aid managerDSS: aid manager ES: replace managerES: replace manager
IssueIssue
Does your company use Does your company use Expert Systems (ES)?Expert Systems (ES)? How do they?How do they? How might they?How might they?
WHAT ARE YOUR WHAT ARE YOUR EXPERIENCES?EXPERIENCES?
MYACIN MYACIN Diagnose patient Diagnose patient
symptoms (triage)symptoms (triage) free doctors for free doctors for
high-level taskshigh-level tasks Panel of doctorsPanel of doctors
diagnose sets of symptomsdiagnose sets of symptoms determine causesdetermine causes 62% accuracy62% accuracy
MYACINMYACIN Built ES with rules Built ES with rules
based on panel consensusbased on panel consensus 68% accuracy68% accuracy
Why better than doctors?Why better than doctors? HeuristicsHeuristics
Stock Market ESStock Market ES Reported by Chandler, 1988Reported by Chandler, 1988 Expert in stock market analysisExpert in stock market analysis
15 years experience15 years experience published newsletterpublished newsletter
Asked him to identify data Asked him to identify data used to make recommendationsused to make recommendations
Stock Market ESStock Market ES 50 data elements identified50 data elements identified Reduced to 30Reduced to 30
redundancyredundancy not really usednot really used undependableundependable
Predicted for 6 months of data Predicted for 6 months of data whether stock value would increase, whether stock value would increase, decrease, or stay the samedecrease, or stay the same
Stock Market ESStock Market ES Rule-based ES builtRule-based ES built Discovered that only Discovered that only
15 data elements came into play 15 data elements came into play Refined the ES modelRefined the ES model Results were better than expertResults were better than expert WHY?WHY?
USA Expert Systems USA Expert Systems
Manufacturing Planning:Manufacturing Planning:
HICLASS - Hughes HICLASS - Hughes (process plans, manufacturing instructions)(process plans, manufacturing instructions)
CUTTECH - METCUT CUTTECH - METCUT (plans for machining operations)(plans for machining operations)
XPSE-E - CAM-I XPSE-E - CAM-I (plans for part fabrication)(plans for part fabrication)
USA Expert Systems USA Expert Systems
Manufacturing Control:Manufacturing Control:
IMACS - DEC IMACS - DEC (plans for computer hardware fabrication (plans for computer hardware fabrication and assembly) and assembly)
IFES - Hughes IFES - Hughes (models dynamic flow of factory information)(models dynamic flow of factory information)
USA Expert Systems USA Expert Systems Factory Automation:Factory Automation:Move - Industrial Technology Move - Industrial Technology Institute Institute (material handling)(material handling)
Dispatcher - Carnegie Group, Inc. Dispatcher - Carnegie Group, Inc. (materials handling system)(materials handling system)
GMR - GM Corp. GMR - GM Corp. (flexible automation assembly system)(flexible automation assembly system)
FMS/CML - Westinghouse FMS/CML - Westinghouse (simulation for FMS design, planning, control)(simulation for FMS design, planning, control)
IssueIssue““Expert systems are Expert systems are
dangerous. People are dangerous. People are likely to be dependent on likely to be dependent on them rather than think them rather than think for themselves.”for themselves.”
WHAT DO YOU THINK?WHAT DO YOU THINK?