<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article
  PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20120330//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML"
         xmlns:xlink="http://www.w3.org/1999/xlink"
         article-type="research-article"
         dtd-version="1.2"
         xml:lang="en">
   <front>
      <journal-meta>
         <journal-id>ZYGO</journal-id>
         <journal-title-group>
            <journal-title>Zygon®</journal-title>
            <abbrev-journal-title/>
         </journal-title-group>
         <issn pub-type="print">0591-2385</issn>
         <issn pub-type="electronic">1467-9744</issn>
      </journal-meta>
      <article-meta>
         <article-id pub-id-type="doi">10.1111/j.1467-9744.1985.tb00604.x</article-id>
         <title-group>
            <article-title>CURRENT DEVELOPMENTS IN ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS</article-title>
         </title-group>
         <contrib-group>
            <contrib contrib-type="author">
               <name name-style="western">
                  <surname>Michie</surname>
                  <given-names>Donald</given-names>
               </name>
            </contrib>
         </contrib-group>
         <aff id="a1"/>
         <pub-date publication-format="electronic" iso-8601-date="1985-12-02">
            <day>02</day>
            <month>12</month>
            <year>1985</year>
         </pub-date>
         <volume>20</volume>
         <issue>4</issue>
         <issue-id pub-id-type="doi">10.1111/zygo.1985.20.issue-4</issue-id>
         <fpage>375</fpage>
         <lpage>389</lpage>
         <permissions/>
         <abstract>
            <p>Abstract.  The definition of an expert system as a knowledge‐based source of advice and explanation pinpoints the critical problem which confronts the would‐be builders of such systems. How is the required body of knowledge to be elicited from its human possessors in a form sufficiently complete for effective organization in computer memory? This article reviews recent advances in the art of automated knowledge‐extraction from expert‐supplied example decisions. Computer induction, as the new approach is called, promises both important parallels to the human capacity for concept formation and also commercial exploitability.</p>
         </abstract>
         <counts/>
      </article-meta>
   </front>
   <body/>
   <back>
      <ref-list>
         <ref id="b1">
            <mixed-citation id="cit1" publication-type="other">Chilausky, R., 
B.Jacobsen, and 
R. S.Michalski. 1976. “<source>An Application of Variable‐Valued Logic to Inductive Learning of Plant Disease Diagnostic Rules 
        </source>.” Proceedings of the Sixth Annual International Symposium on Multi‐Variable Logic, Utah.
</mixed-citation>
         </ref>
         <ref id="b2">
            <mixed-citation id="cit2" publication-type="book">Feigenbaum, E. A.1977. The Art of Artificial Intelligence I: Therms and Case Studies of Knowledge Engineering. Pub. no. STAN‐CS‐77‐621. 
            Stanford
            , 
            Calif.
          : Stanford University, Dept. of Computer Science.
</mixed-citation>
         </ref>
         <ref id="b3">
            <mixed-citation id="cit3" publication-type="book">Hunt, E. B., 
J.Marin, and 
P.Stone. 1966. Experiments in Induction. 
            New York
          : Academic Press.
</mixed-citation>
         </ref>
         <ref id="b4">
            <mixed-citation id="cit4" publication-type="journal">Michalski, R. S. and 
R. L.Chilausky. 1980a. “Knowledge Acquisition by Encoding Expert Rules Versus Computer Induction from Examples: A Case Study Involving Soybean Pathology. 
<source>International Journal of Man-Machine Studies 
        </source>12:63–87.
</mixed-citation>
         </ref>
         <ref id="b5">
            <mixed-citation id="cit5" publication-type="journal">Michalski, R. S. and 
R. L.Chilausky. 1980. “Learning by Being Told and Learning from Examples: An Experimental Comparison of the Two Methods of Knowledge Acquisition in the Context of Developing an Expert System for Soybean Disease Diagnosis. 
<source>International Journal of Policy Analysis and Information Systems 
        </source>4:125–61.
</mixed-citation>
         </ref>
         <ref id="b6">
            <mixed-citation id="cit6" publication-type="book">Michie, D., 
S.Muggleton, 
C.Riese, and 
S.Zubrick. 1984. “<source>RuleMaster: A Second‐Generation Knowledge‐Engineering Facility 
        </source>.” In First Conference on Artificial Intelligence Applications, Denver, 5–7 December 1984, 591–97. 
            Silver Spring
            , 
            Md.
          : IEEE Computer Society.
</mixed-citation>
         </ref>
         <ref id="b7">
            <mixed-citation id="cit7" publication-type="other">Muggleton, S.1985. “<source>Inductive Acquisition of Expert Knowledge 
        </source>.” Ph.D. diss., University of Edinburgh.
</mixed-citation>
         </ref>
         <ref id="b8">
            <mixed-citation id="cit8" publication-type="book">Quinlan, J. R.1983. “<source>Learning Efficient Classification Procedures and Their Application to Chess End Games 
        </source>.” In Machine Learning: An Artificial Intelligence Approach, ed. 
R. S.Michalski, 
J. G.Carbonell, and 
T. M.Mitchell, 463–82. 
            Palo Alto
            , 
            Calif.
          : Tioga.
</mixed-citation>
         </ref>
         <ref id="b9">
            <mixed-citation id="cit9" publication-type="book">Shapiro, A. and 
D.Michie. in press. “<source>A Self‐Commenting Facility for Inductively Synthesised Endgame Expertise 
        </source>.” In Advances in Computer Chess, 4, ed. 
D.Beal. 
            Oxford
          : Pergamon.
</mixed-citation>
         </ref>
         <ref id="b10">
            <mixed-citation id="cit10" publication-type="book">Shapiro, A.T.Niblett. 1982. “<source>Automatic Induction of Classification Rules for a Chess Endgame 
        </source>.” In Advances in Computer Chess, 3, ed. 
M. R. B.Clarke. 
            Oxford
          : Pergamon.
</mixed-citation>
         </ref>
      </ref-list>
   </back>
</article>
