Unifying Expert Systems and the Decision Sciences

There are many tools and much literature that combine the expert systems and mathematical modeling paradigms. This survey focuses on a subset consisting of: decision making and unification, and not mere co-existence, of the two approaches. The unification effort is new and presents many research challenges at the theoretical, methodological, and tool levels. At the theoretical level, accepted prescriptions now exist that stipulate in which situations it is valid to use various forms of mathematical and qualitative reasoning. This is leading to a unified theory of the decision sciences for problems spanning choice, forecasting, risk assessment, design, operations, and many others. At the tool level three forms of synthesis of expert systems and mathematical models are particularly noteworthy: knowledge-based decision aids, intelligent decision modeling systems, and decision analytic expert systems. This survey gives definitions, surveys, and examples of each of these ways of unifying expert systems and modeling. Following this are lessons learned and further research needs. A great deal of synthesis work remains to be done, and a goal of this survey is to highlight some of the issues and invite discussion.

[1]  M O'Neil,et al.  Evaluating and validating very large knowledge-based systems. , 1990, Medical informatics = Medecine et informatique.

[2]  Terry Winograd,et al.  Understanding computers and cognition - a new foundation for design , 1987 .

[3]  David Heckerman,et al.  Probabilistic similarity networks , 1991, Networks.

[4]  Barry G. Silverman,et al.  Criticism-Based Knowledge Acquisition for Document Generation , 1991, IAAI.

[5]  D. Bunn,et al.  Interaction of judgemental and statistical forecasting methods: issues & , 1991 .

[6]  B. G. Silverman Expert intuition and ill-structured problem solving , 1985, IEEE Transactions on Engineering Management.

[7]  J. Fox,et al.  Alternatives to Bayes? , 1980, Methods of Information in Medicine.

[8]  A. Tversky,et al.  On the psychology of prediction , 1973 .

[9]  John Gaschnig,et al.  MODEL DESIGN IN THE PROSPECTOR CONSULTANT SYSTEM FOR MINERAL EXPLORATION , 1981 .

[10]  Dominic A. Clark,et al.  Using predicate logic to integrate qualitative reasoning and classical decision theory , 1990, IEEE Trans. Syst. Man Cybern..

[11]  Milan Zeleny,et al.  Cognitive Equilibirum: A New Paradigm of Decision Making? , 1989 .

[12]  Janet L. Kolodner,et al.  Improving Human Decision Making through Case-Based Decision Aiding , 1991, AI Mag..

[13]  Ronald A. Howard,et al.  Readings on the Principles and Applications of Decision Analysis , 1989 .

[14]  Kristian G. Olesen,et al.  HUGIN - A Shell for Building Bayesian Belief Universes for Expert Systems , 1989, IJCAI.

[15]  Eric Horvitz,et al.  Decision Analysis and Expert Systems , 1991, AI Mag..

[16]  Max Henrion,et al.  An Experimental Comparison of Knowledge Engineering for Expert Systems and for Decision Analysis , 1987, AAAI.

[17]  Steen Andreassen,et al.  MUNIN - A Causal Probabilistic Network for Interpretation of Electromyographic Findings , 1987, IJCAI.

[18]  R. Dawes Judgment under uncertainty: The robust beauty of improper linear models in decision making , 1979 .

[19]  Edward H. Shortliffe,et al.  Computer-based medical consultations, MYCIN , 1976 .

[20]  Ramayya Krishnan,et al.  A knowledge-based mathematical model formulation system , 1992, CACM.

[21]  Peter Szolovits,et al.  Categorical and Probabilistic Reasoning in Medical Diagnosis , 1990, Artif. Intell..

[22]  John Fox,et al.  Logic engineering for knowledge engineering: design and implementation of the Oxford System of Medicine , 1990, Artif. Intell. Medicine.

[23]  Fred Collopy,et al.  Rule-Based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations , 1992 .

[24]  Jayant Kalagnanam,et al.  A comparison of decision alaysis and expert rules for sequential diagnosis , 2013, UAI.

[25]  Ben P. Wise An experimental comparison of uncertain inference systems (artificial intelligence, probability, entropy) , 1986 .

[26]  田中 穂積 E.H.Shortliffe 著, "Computer-Based Medical Consultations : MYCIN", American Elsevier, A4判, 264ぺージ, \10,080, 1976 , 1978 .

[27]  Paul J. Krause,et al.  Formal specifications and medical decision support systems , 1993, Appl. Artif. Intell..

[28]  F E Masarie,et al.  Quick medical reference (QMR) for diagnostic assistance. , 1986, M.D.Computing.

[29]  Eugene Charniak,et al.  Bayesian Networks without Tears , 1991, AI Mag..

[30]  Efraim Turban,et al.  Decision support and expert systems , 1993 .

[31]  Joyce J. Elam,et al.  Can Software Influence Creativity? , 1990, Inf. Syst. Res..