12,015 research outputs found
Turing Automata and Graph Machines
Indexed monoidal algebras are introduced as an equivalent structure for
self-dual compact closed categories, and a coherence theorem is proved for the
category of such algebras. Turing automata and Turing graph machines are
defined by generalizing the classical Turing machine concept, so that the
collection of such machines becomes an indexed monoidal algebra. On the analogy
of the von Neumann data-flow computer architecture, Turing graph machines are
proposed as potentially reversible low-level universal computational devices,
and a truly reversible molecular size hardware model is presented as an
example
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A generalized characterization of algorithmic probability
An a priori semimeasure (also known as "algorithmic probability" or "the
Solomonoff prior" in the context of inductive inference) is defined as the
transformation, by a given universal monotone Turing machine, of the uniform
measure on the infinite strings. It is shown in this paper that the class of a
priori semimeasures can equivalently be defined as the class of
transformations, by all compatible universal monotone Turing machines, of any
continuous computable measure in place of the uniform measure. Some
consideration is given to possible implications for the prevalent association
of algorithmic probability with certain foundational statistical principles
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