Abstract
Computational learning theory is concerned with developing “scratch” a probably approximately correct (PAC) algorithm to solve a given computational problem. Program error detection /correction is concerned with transforming programs — such as these — which are correct on most instances into programs that are correct on all instances. The two approaches together enable one to generate a perfect program from scratch. The goal of this talk is to describe how this latter error detection/correction of algorithms works, and to encourage its integration into learning theory.
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© 1997 Springer-Verlag Berlin Heidelberg
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Blum, M. (1997). Program error detection/correction: Turning PAC learning into Perfect learning. In: Li, M., Maruoka, A. (eds) Algorithmic Learning Theory. ALT 1997. Lecture Notes in Computer Science, vol 1316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63577-7_31
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DOI: https://doi.org/10.1007/3-540-63577-7_31
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