ebook img

Intelligent Decision Making: An AI-Based Approach PDF

410 Pages·2008·12.23 MB·English
Save to my drive
Quick download
Download
Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.

Preview Intelligent Decision Making: An AI-Based Approach

Gloria Phillips-Wren, Nikhil Ichalkaranje and Lakhmi C. Jain (Eds.) Intelligent Decision Making: An AI-Based Approach StudiesinComputationalIntelligence,Volume97 Editor-in-chief Prof.JanuszKacprzyk SystemsResearchInstitute PolishAcademyofSciences ul.Newelska6 01-447Warsaw Poland E-mail:[email protected] Furthervolumesofthisseriescanbefoundonour Vol.86.ZbigniewLesandMogdalenaLes homepage:springer.com ShapeUnderstandingSystems,2008 ISBN978-3-540-75768-9 Vol.74.RobertSchaefer Vol.87.YuriAvramenkoandAndrzejKraslawski FoundationofGlobalGeneticOptimization,2007 CaseBasedDesign,2008 ISBN978-3-540-73191-7 ISBN978-3-540-75705-4 Vol.75.CrinaGrosan,AjithAbrahamandHisaoIshibuchi Vol.88.TinaYu,DavidDavis,CemBaydarandRajkumar (Eds.) Roy(Eds.) HybridEvolutionaryAlgorithms,2007 EvolutionaryComputationinPractice,2008 ISBN978-3-540-73296-9 ISBN978-3-540-75770-2 Vol.76.SubhasChandraMukhopadhyayandGourabSen Vol.89.ItoTakayuki,HattoriHiromitsu,ZhangMinjie Gupta(Eds.) andMatsuoTokuro(Eds.) AutonomousRobotsandAgents,2007 Rational,Robust,Secure,2008 ISBN978-3-540-73423-9 ISBN978-3-540-76281-2 Vol.77.BarbaraHammerandPascalHitzler(Eds.) Vol.90.SimoneMarinaiandHiromichiFujisawa(Eds.) PerspectivesofNeural-SymbolicIntegration,2007 MachineLearninginDocumentAnalysis ISBN978-3-540-73953-1 andRecognition,2008 Vol.78.CostinBadicaandMarcinPaprzycki(Eds.) ISBN978-3-540-76279-9 IntelligentandDistributedComputing,2008 Vol.91.HorstBunke,KandelAbrahamandLastMark(Eds.) ISBN978-3-540-74929-5 AppliedPatternRecognition,2008 Vol.79.XingCaiandT.-C.JimYeh(Eds.) ISBN978-3-540-76830-2 QuantitativeInformationFusionforHydrological Vol.92.AngYang,YinShanandLamThuBui(Eds.) Sciences,2008 SuccessinEvolutionaryComputation,2008 ISBN978-3-540-75383-4 ISBN978-3-540-76285-0 Vol.80.JoachimDiederich Vol.93.ManolisWallace,MariosAngelidesandPhivos RuleExtractionfromSupportVectorMachines,2008 Mylonas(Eds.) ISBN978-3-540-75389-6 AdvancesinSemanticMediaAdaptationand Vol.81.K.Sridharan Personalization,2008 RoboticExplorationandLandmarkDetermination,2008 ISBN978-3-540-76359-8 ISBN978-3-540-75393-3 Vol.94.ArpadKelemen,AjithAbrahamandYuehuiChen Vol.82.AjithAbraham,CrinaGrosanandWitold (Eds.) Pedrycz(Eds.) ComputationalIntelligenceinBioinformatics,2008 EngineeringEvolutionaryIntelligentSystems,2008 ISBN978-3-540-76802-9 ISBN978-3-540-75395-7 Vol.95.Radu Dogaru Vol.83.BhanuPrasadandS.R.M.Prasanna(Eds.) Systematic Design for Emergence in Cellular Nonlinear Speech,Audio,ImageandBiomedicalSignalProcessing Networks, 2008 usingNeuralNetworks,2008 ISBN978-3-540-76800-5 ISBN978-3-540-75397-1 Vol.96.Aboul Ella Hassanien, Ajith Abraham and Janusz Vol.84.MarekR.OgielaandRyszardTadeusiewicz Kacprzyky(Eds.) ModernComputationalIntelligenceMethods Computational Intelligence in Multimedia Processing: fortheInterpretationofMedicalImages,2008 Recent Advances,2008 ISBN978-3-540-75399-5 ISBN978-3-540-76826-5 Vol.85.ArpadKelemen,AjithAbrahamandYulanLiang Vol.97.Gloria Phillips-Wren, Nikhil Ichalkaranje and (Eds.) Lakhmi C. Jain (Eds.) ComputationalIntelligenceinMedicalInformatics,2008 IntelligentDecision Making: An AI-Based Approach,2008 ISBN978-3-540-75766-5 ISBN978-3-540-76829-9 Gloria Phillips-Wren Nikhil Ichalkaranje Lakhmi C. Jain (Eds.) Intelligent Decision Making: An AI-Based Approach With107Figuresand44Tables 123 Prof. Dr. Gloria Phillips-Wren Dr. Nikhil Ichalkaranje Information Systems and Operations Management School of Electrical The Sellinger School of Business and Management and Information Engineering Loyola College in Maryland University of South Australia 4501 N. Charles Street Adelaide Baltimore, MD 21210 South Australia SA 5095 USA Australia Prof. Dr. Lakhmi C. Jain School of Electrical and Information Engineering University of South Australia Adelaide South Australia SA 5095 Australia ISBN978-3-540-76828-9 e-ISBN978-3-540-76829-6 StudiesinComputationalIntelligenceISSN1860-949X LibraryofCongressControlNumber:2007939887 (cid:1)c 2008Springer-VerlagBerlinHeidelberg Thisworkissubjecttocopyright.Allrightsarereserved,whetherthewholeorpartofthematerial isconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation,broad- casting,reproductiononmicrofilmorinanyotherway,andstorageindatabanks.Duplicationof thispublicationorpartsthereofispermittedonlyundertheprovisionsoftheGermanCopyrightLaw ofSeptember9,1965,initscurrentversion,andpermissionforusemustalwaysbeobtainedfrom Springer-Verlag.ViolationsareliabletoprosecutionundertheGermanCopyrightLaw. Theuseofgeneraldescriptivenames,registerednames,trademarks,etc.inthispublicationdoesnot imply, even in the absence of a specific statement, that such names are exempt from the relevant protectivelawsandregulationsandthereforefreefor general use. CoverDesign:Deblik,Berlin,Germany Printedonacid-freepaper 9 8 7 6 5 4 3 2 1 springer.com Dedicated to our mothers who were our first and best teachers. Preface Thefusionofartificialintelligence(AI)withdecisionsupportsystems(DSSs) is opening exciting new areas of research and application. The resulting sys- tems are smarter, more efficient, adaptable, and better able to aid human decision making. While AI aims to mimic human behaviour in limited ways, DSSs attempt to help humans make the best choice among a set of possible choices given explicit or implied criteria. Long a topic of science fiction, AI today is demonstrating that it can be integrated effectively into real systems and that it offers the only way possible to capture aspects of human intelli- gence such as learning.The combinationof AI and DSSs provides formidable new computational assistants to humans that extend their capabilities in routine and complex stressful environments. Due to the increasing matu- rity of this interdisciplinary field as evidenced by the recent growth in the number of research publications and contributors entering the field, a book that explores the current state and future outlook of intelligent DSSs seems appropriate. Thebookisorganizedaroundthreethemes.Thefirsttwochaptersprovide asolidfoundationbyexploringstudiesandtheoriesofhumandecisionmaking. They trace some one hundred years of research including recent work by the well-known authors and provide a vision of the use of computerized decision aids.ThesecondsectiondealswithparadigmsandmethodsassociatedwithAI in DSS. The final section provides sample applications among the many that are appearing today and gives our perspective on future research directions needed to advance the field. Thisbookwouldnothavebeenpossiblewithouttheeffortsofmanypeople. We thank the contributors for their inspiring research and the reviewers for their efforts to create a high-quality book. The publisher’s support, patience andassistancearegratefullyacknowledged.Inparticular,SrilathaAchuthan’s unwaveringeffortsasprojectmanagerprovidedhelpwhenweneededitmost. VIII Preface We thankthe researchcommunityforthe advancesthathavemadethis book possible and our families for their continued support. USA Gloria Phillips-Wren Australia Nikhil Ichalkaranje Australia Lakhmi C. Jain Foreword Intelligentdecisionsystems(IDS)arearelativelynewparadigminthedecision supportsystems(DSS) area.Consistentwiththe modernviewonworkactiv- ityasmostly‘knowledgework’(Davenport,2005)andrecognisingthe critical role of knowledge for effective decision-making, intelligent decision support aims to provide the decision maker with quality assistance in gaining better knowledge and understanding of the decisionsituation. IDS are the means to achieve such assistance. This needfor knowledgemanagementandprocessingwithin decisionsup- port systems has resulted in a special class of systems that incorporates qualitative knowledge and reasoning, extending the functionality beyond those traditionally covered by DSS applications. These systems, variously termed Intelligent Decision Support Systems, Intelligent Decision Systems, Knowledge-BasedDecisionSupportSystems,ActiveDSSandJointCognitive Systems, include qualitative knowledge to extend the typically quantitative data ofearlierapproachesto decisionsupport(BursteinandHolsapple,2008; Gupta et al. 2006). The label intelligent in IDS is derived from the attempts made in artifi- cial intelligence (AI) to develop systems that computationally emulate some human cognitive capabilities such as reasoning, learning and memory. The need to incorporate domain knowledge and intelligent capabilities in deci- sion support systems has been identified in various forms and models by many researchers, starting from Simon (1977), followed by Sprague (1993), and exemplified by Turban, Aronson and Liang (2005) and Holsapple and Whinston (1996) in their comprehensive analyses of tools and techniques for incorporatingintelligenceintoDSS.ArnottandPervan(2005),intheirreview of the DSS field, traced and described Intelligent Decision Support as a sep- arate branch, which originated from research in AI and Expert Systems to complement the needs of modern PersonalisedDecision Support. The main role of IDS in an organisation is as an enabler for knowledge processingwithcommunicationcapabilitiestosupportknowledgesharingand exchangeandtofacilitateorganisationallearning(CarlssonandKalling,2006; X Foreword Bursteinand Linger,2003).IDS aimto assistthe decisionmaker in overcom- ingcognitivelimitationstoachievingthebestdecisionoutcomes.Atthesame time the system could identify some useful knowledge for future improve- ments in the decision-making process, thus facilitating continuous learning processes by an organisation.ConventionalDSS was not intended to support such functionality, hence giving rise to IDS in a knowledge management con- text. Despite the significant potential of IDS and remarkable advances in AI technologies, the promise of IDS has not yet been realized. IDSarenotwidespreadassuch.Onereasonisthatcomprehensiveresearch is still required on AI technologies to be used in IDS. Some technologies such as intelligent agents have advanced to the point that they are imple- mented in numerous practical applications, while other AI concepts such as neural networks are not yet as mature. In most cases, specialized IDS appli- cations are reported in the literature, although generalized applications have notbeendeveloped.Researchisneededonarchitecturesandframeworksthat could support production-level IDS both at the AI and at systems levels. Although IDS do not in general exist as stand-alone systems, any large-scale management information system would include some intelligent components. Modern approaches to assisting organizations such as customer relationship management (CRM), knowledge management systems (KMS), and business intelligence (BI) systems are heavily influenced by intelligent techniques and include a wide range of intelligent systems functionality. Many such systems requireaccesstoexpertorproblem-domainknowledge.Availabilityofsophis- ticated generic technological infrastructure makes it easier to specialise such systems to suit specific application domains. A number of books have been published in the area of IDS and related areas of Intelligent Decision Support Systems, and one needs to ask what another book can add to the community. Publication patterns over the last 10years(showninFig.1basedondatafromGoogleScholar)appeartoshow continuedinterestinIDS.Thisisamuchneededbooktoupdatetheinterested reader in an exciting research field with many opportunities for advances in both theoretical and applied areas. The current volume is an effort to bridge the range of exploration in this field from fundamental understanding of human decision making at an abstract conceptual level, to methods of computational intelligence, and to applicationsofintelligentdecisionsupporttechniquesinspecificcontexts.The bookpresentsfascinatingbackgroundinformationonhumandecisionmaking and makes a contribution to the IDS area by presenting the current state of knowledgeand identifying key researchgaps.I would like to congratulatethe editors of this book and look forward to it being remembered as a pivotal beginning for collective focus and mutual inspiration. Victoria, Australia Frada V. Burstein Foreword XI 25,000 20,000 15,000 intelligent decision support intelligent decision support systems 10,000 intelligent decision systems 5,000 0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 Fig.1.ComparativedataonpublicationsinIntelligentDecisionSupport,Intelligent DecisionSupportSystemsandIntelligentDecisionSystems(basedonthedatafrom Google Scholar) References Arnott,D.andPervan,G.(2005). ACritical Analysisof Decision SupportSystems Research. Journal of Information Technology, 20, 67–87. Burstein, F. and Holsapple, C.W. (eds.) (2008). Handbook on Decision Support Systems. Berlin/Heidelberg: Springer. Burstein, F. and Linger, H. (2003). Supporting Post-Fordist Work Practices: A KnowledgeManagement FrameworkforSupportingKnowledgeWork.Informa- tion Technology and People, 16, 3, 289–305. Carlsson, S.A. and Kalling, T. (2006). Decision Support through Knowledge Man- agement: What Works and What Breaks. In Adam, F., Br´ezillon, P., Carlsson, S.andHumphreys,P.(eds.),Creativity and Innovation inDecisionMaking and Decision Support, London, UK:Decision Support Press, 693–710. Davenport,T.H.(2005).ThinkingforaLiving:HowtoGetBetterPerformanceand Results from Knowledge Workers. Boston, MA: Harvard Business School Press. GuptaJ.,ForgionneG.,andMoraM.(eds.)(2006).IntelligentDecision-MakingSup- port Systems (i-DMSS): Foundations, Applications and Challenges.Engineering Decision Series of Springer. Simon, H. (1977). The New Science of Management Decisions. New Jersey, NJ: Prentice-Hall. Sprague, R.H. (1993). A Framework for the Development of Decision Support Sys- tems. In Sprague, R.H. and Watson, H.J. (eds.), Decision Support Systems PuttingTheoryintoPractice,NewJersey,NJ:Prentice-HallInternational,3–26. Turban, E., Aronson, J. and Liang, T. (2005). Decision Support Systems and Intelligence Systems. 7th Ed., New Jersey: Pearson Prentice-Hall. Holsapple C. and Whinston, A. (1996). Decision Support Systems: A Knowledge Based Approach. St.Paul, MN:West Publishing.

Description:
Intelligent Decision Support Systems have the potential to transform human decision making by combining research in artificial intelligence, information technology, and systems engineering. The field of intelligent decision making is expanding rapidly due, in part, to advances in artificial intellig
See more

The list of books you might like

Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.