
TL;DR
This paper develops a comprehensive resource-bounded measure theory for complexity classes, extending classical measure concepts to computational settings and establishing properties like additivity, invariance, and a zero-one law.
Contribution
It introduces a resource-bounded measure framework using type-2 martingales applicable to various complexity classes, unifying measure theory with computational complexity.
Findings
Defines $ u$-measurable sets within complexity classes
Proves a resource-bounded zero-one law for invariant sets
Establishes measure properties like additivity and closure under operations
Abstract
A general theory of resource-bounded measurability and measure is developed. Starting from any feasible probability measure on the Cantor space and any suitable complexity class , the theory identifies the subsets of that are -measurable in and assigns measures to these sets, thereby endowing with internal measure-theoretic structure. Classes to which the theory applies include various exponential time and space complexity classes, the class of all decidable languages, and the Cantor space itself, on which the resource-bounded theory is shown to agree with the classical theory. The sets that are -measurable in are shown to form an algebra relative to which -measure is well-behaved. This algebra is also shown to be complete and closed under sufficiently uniform infinitary unions and intersections, and -measure in is…
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Benford’s Law and Fraud Detection · semigroups and automata theory
