Abstract
In this paper, we reconsider the definitions of procrastinating learning machines. In the original definition of Freivalds and Smith [FS93], constructive ordinals are used to bound mindchanges. We investigate the possibility of using arbitrary linearly ordered sets to bound mindchanges in a similar way. It turns out that using certain ordered sets it is possible to define inductive inference types more general than the previously known ones. We investigate properties of the new inductive inference types and compare them to other types.
This research was supported by Latvian Science Council Grant No.93.599 and NSF Grant 9421640.
The third author was supported in part by NSF Grant 9301339.
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Ambainis, A., Freivalds, R., Smith, C.H. (1996). General inductive inference types based on linearly-ordered sets. In: Puech, C., Reischuk, R. (eds) STACS 96. STACS 1996. Lecture Notes in Computer Science, vol 1046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-60922-9_21
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DOI: https://doi.org/10.1007/3-540-60922-9_21
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