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ABSTRACT
The number of steps required to compute a function depends, in general, on the type of computer that is used, on the choice of computer program, and on the input-output code. Nevertheless, the results obtained in this paper are so general as to be nearly independent of these considerations.
A function is exhibited that requires an enormous number of steps to be computed, yet has a “nearly quickest” program: Any other program for this function, no matter how ingeniously designed it may be, takes practically as many steps as this nearly quickest program.
A different function is exhibited with the property that no matter how fast a program may be for computing this function another program exists for computing the function very much faster.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 93
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Efim Kinber , Christophe Papazian , Carl Smith , Rolf Wiehagen, On the intrinsic complexity of learning recursive functions, Proceedings of the twelfth annual conference on Computational learning theory, p.257-266, July 07-09, 1999, Santa Cruz, California, United States
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Sanjay Jain , Arun Sharma, Elementary formal systems, intrinsic complexity, and procrastination, Proceedings of the ninth annual conference on Computational learning theory, p.181-192, June 28-July 01, 1996, Desenzano del Garda, Italy
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Nancy Lynch , Albert Meyer , Michael Fischer, Sets that don't help, Proceedings of the fifth annual ACM symposium on Theory of computing, p.130-134, April 30-May 02, 1973, Austin, Texas, United States
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