Axiomatizing Resource Bounds for Measure
Xiaoyang Gu, Jack H. Lutz, Satyadev Nandakumar, James S. Royer

TL;DR
This paper develops a rigorous framework for resource bounds in resource-bounded measure, replacing example-based approaches with a set of closure properties that characterize resource bounds, including those used in time and space hierarchies.
Contribution
It provides a characterization of resource bounds for measure via closure properties, unifying various classes under a common theoretical framework.
Findings
Every class with Mehlhorn's closure properties is a resource bound.
Type-2 time and space hierarchies have these closure properties.
The resource bounds used in measure are robust and well-founded.
Abstract
Resource-bounded measure is a generalization of classical Lebesgue measure that is useful in computational complexity. The central parameter of resource-bounded measure is the {\it resource bound} , which is a class of functions. When is unrestricted, i.e., contains all functions with the specified domains and codomains, resource-bounded measure coincides with classical Lebesgue measure. On the other hand, when contains functions satisfying some complexity constraint, resource-bounded measure imposes internal measure structure on a corresponding complexity class. Most applications of resource-bounded measure use only the "measure-zero/measure-one fragment" of the theory. For this fragment, can be taken to be a class of type-one functions (e.g., from strings to rationals). However, in the full theory of resource-bounded measurability and measure, the…
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Taxonomy
TopicsComputability, Logic, AI Algorithms · Complexity and Algorithms in Graphs · Algorithms and Data Compression
