Asymptotic behavior and halting probability of Turing Machines
Germano D'Abramo
Abstract
Through 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.
Create a lesson
Related papers
The Mysteries of Plato's Parmenides Dispersed: From musical intervals to contacts/"hapseis" to "logoi"
Stelios Negrepontis
On the Babylonian Division of Trapezoids
Franz Lemmermeyer
Explanations, Prompts, and Formalizations: Arguments for New Norms in LLM-Enabled Mathematical Research
Axel Boldt
Mohsen Hachtroudi and the Geometry of Differential Equations
Masoud Khalkhali
The Mathematician Leads: Building a Research Profile in the Age of Frontier AI
Helmut H. W. Hofer
On the Egyptian knotted rope
Rubén Vigara