Generality in artificial intelligence

@article{McCarthy1987GeneralityIA,
  title={Generality in artificial intelligence},
  author={John McCarthy},
  journal={Commun. ACM},
  year={1987},
  volume={30},
  pages={1029-1035}
}
  • J. McCarthy
  • Published 1 December 1987
  • Computer Science
  • Commun. ACM
My 1971 Turing Award Lecture was entitled "Generality in Artificial Intelligence." The topic turned out to have been overambitious in that I discovered I was unable to put my thoughts on the subject in a satisfactory written form at that time. It would have been better to have reviewed my previous work rather than attempt something new, but such was not my custom at that time. I am grateful to ACM for the opportunity to try again. Unfortunately for our science, although perhaps fortunately for… 
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References

SHOWING 1-10 OF 46 REFERENCES
SOME PHILOSOPHICAL PROBLEMS FROM THE STANDPOINT OF ARTI CIAL INTELLIGENCE
Some Expert Systems Need Common Sense
  • J. McCarthy
  • Medicine
    Annals of the New York Academy of Sciences
  • 1984
TLDR
The object of this lecture is to describe common sense abilities and the problems that require them in an expert system, a program for advising physicians on treating bacterial infections of the blood and meningitis.
A Logic for Default Reasoning
  • R. Reiter
  • Philosophy, Computer Science
    Artif. Intell.
  • 1980
Applications of Circumscription to Formalizing Common Sense Knowledge
Non-Monotonic Logic I
First Order Theories of Individual Concepts and Propositions.
We discuss rst order theories in which individual concepts are admitted as mathematical objects along with the things that reify them. This allows very straightforward formalizations of knowledge,
A Learning Machine: Part II
An effort is made to improve the performance of the learning machine described in Part I, and the over-all effect of various changes is considered. Comparative runs by machines without the scoring
Truth Maintenance Systems for Problem Solving
TLDR
It is shown that reasoning programs which take care to record the logical justifications for program beliefs can apply several powerful, but simple, domain-independent algorithms to maintain the consistency of program beliefs and realize substantial search efficiencies.
...
...