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[[Edward Feigenbaum]] said:
* "In the knowledge lies the power."<ref name="Feigenbaum">{{Cite journal| doi = 10.1145/1743546.1743564| issn = 0001-0782| volume = 53| issue = 6| pages = 41–45| last = Shustek| first = Len| title = An interview with Ed Feigenbaum| journal = Communications of the ACM| accessdate = 2022-07-14| date = June 2010| s2cid = 10239007| url = https://dl.acm.org/doi/10.1145/1743546.1743564| url-access = subscription}}</ref>
to describe that high performance in a specific ___domain requires both general and highly ___domain-specific knowledge. Ed Feigenbaum and Doug Lenat called this The Knowledge Principle:
{{Blockquote
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We did not have a grandiose vision. We worked bottom up. Our chemist was [[Carl Djerassi]], inventor of the chemical behind the birth control pill, and also one of the world's most respected mass spectrometrists. Carl and his postdocs were world-class experts in mass spectrometry. We began to add to their knowledge, inventing knowledge of engineering as we went along. These experiments amounted to titrating DENDRAL more and more knowledge. The more you did that, the smarter the program became. We had very good results.
The generalization was: in the knowledge lies the power. That was the big idea. In my career that is the huge, "Ah ha!," and it wasn't the way AI was being done previously. Sounds simple, but it's probably AI's most powerful generalization.<ref name="Feignebaum Interview">{{Cite journal| doi = 10.1145/1743546.1743564| issn = 0001-0782| volume = 53| issue = 6| pages = 41–45| last = Shustek| first = Len| title = An interview with Ed Feigenbaum| journal = Communications of the ACM| accessdate = 2022-08-05| date = 2010| s2cid = 10239007| url = https://cacm.acm.org/magazines/2010/6/92472-an-interview-with-ed-feigenbaum/fulltext| url-access = subscription}}</ref>}}
The other expert systems mentioned above came after DENDRAL. MYCIN exemplifies the classic expert system architecture of a knowledge-base of rules coupled to a symbolic reasoning mechanism, including the use of certainty factors to handle uncertainty. GUIDON shows how an explicit knowledge base can be repurposed for a second application, tutoring, and is an example of an [[intelligent tutoring system]], a particular kind of knowledge-based application. Clancey showed that it was not sufficient simply to use [[MYCIN]]'s rules for instruction, but that he also needed to add rules for dialogue management and student modeling.{{sfn|Clancey|1987}} XCON is significant because of the millions of dollars it saved [[Digital Equipment Corporation|DEC]], which triggered the expert system boom where most all major corporations in the US had expert systems groups, to capture corporate expertise, preserve it, and automate it:
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== References ==
* {{Cite journal| doi = 10.1016/0004-3702(91)90053-M| issn = 0004-3702| volume = 47| issue = 1| pages = 139–159| last = Brooks| first = Rodney A.| title = Intelligence without representation| journal = Artificial Intelligence| accessdate = 2022-09-13| date = 1991| s2cid = 207507849| url = https://dx.doi.org/10.1016/0004-3702%2891%2990053-M| url-access = subscription}}
* {{Cite book| title = Knowledge-Based Tutoring: The GUIDON Program (MIT Press Series in Artificial Intelligence)| last = Clancey | first = William |year = 1987| edition=Hardcover}}
* {{Crevier 1993}}.
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* {{Citation| arxiv = 1606.04422| last1 = Serafini| first1 = Luciano| last2 = Garcez| first2 = Artur d'Avila| title = Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and Knowledge| date = 2016-07-07}}
* {{cite journal |last1=Spiegelhalter |first1=David J. |last2=Dawid |first2=A. Philip |last3=Lauritzen |first3=Steffen |first4=Robert G. |last4=Cowell |author-link1=David Spiegelhalter |author-link3=Steffen Lauritzen |date=1993 |title=Bayesian analysis in expert systems |journal=Statistical Science |volume=8 |issue=3}}
* {{Cite journal |doi=10.1093/mind/LIX.236.433 |issn=0026-4423 |volume=LIX |issue=236 |pages=433–460 |last=Turing |first=A. M. |title=I.—Computing Machinery and Intelligence |journal=Mind |accessdate=2022-09-14 |date=1950 |url=https://doi.org/10.1093/mind/LIX.236.433|url-access=subscription }}
* {{Cite book| pages = 415–422| last = Valiant| first = Leslie G| chapter= Knowledge Infusion: In Pursuit of Robustness in Artificial Intelligence| date = 2008 |editor1=Hariharan, R. |editor2=Mukund, M. |editor3=Vinay, V. |title=Foundations of Software Technology and Theoretical Computer Science (Bangalore)}}
* {{cite conference
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