Asymptotic behavior and halting probability of Turing Machines

dc.creatorD'Abramo, Germano
dc.date2005-12-16
dc.date2006-10-05
dc.date.accessioned2026-07-07T06:55:24Z
dc.date.available2026-07-07T06:55:24Z
dc.descriptionThrough a straightforward Bayesian approach we show that under some general conditions a maximum running time, namely the number of discrete steps performed by a computer program during its execution, can be defined such that the probability that such a program will halt after that time is smaller than any arbitrary fixed value. Consistency with known results and consequences are also discussed.
dc.descriptionPlain LaTeX, 8 pages. In press
dc.identifierhttps://arxiv.org/abs/math/0512390
dc.identifierhttp://arxiv.org/abs/math/0512390
dc.identifierChaos, Solitons & Fractals (2006)
dc.identifierdoi:10.1016/j.chaos.2006.08.022
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/106269
dc.subjectHistory and Overview
dc.titleAsymptotic behavior and halting probability of Turing Machines
dc.typetext

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