Open AccessJournal Article
On Process Complexity.
4
TL;DR: This paper defines a variant of process complexity based on Levin's definition of a process, and proves that strict process complexity does not agree within an additive constant with Schnorr's original process complexity.
read more
Abstract: Process complexity is one of the basic variants of Kolmogorov complexity. Unlike plain Kolmogorov complexity process complexity provides a simple characterization of randomness for real numbers in terms of initial segment complexity. Process complexity was first developed in (Schnorr 1973). Schnorr's definition of a process, while simple, can be difficult to work with. In many situations, a preferable definition of a process is that given by Levin in (Levin & Zvonkin 1970). In this paper we define a variant of process complexity based on Levin's definition of a process. We call this variant strict process complexity. Strict process complexity retains the main desirable properties of process complexity. Particularly, it provides simple characterizations of Martin-Lof random real numbers, and of computable real numbers. However, we will prove that strict process complexity does not agree within an additive constant with Schnorr's original process complexity.
One of the basic properties of prefix-free complexity is that it is subadditive. Subadditive means that there is some constant d such that for all strings σ, τ the complexity of στ (σ and τ concatenated) is less than or equal to the sum of the complexities of σ and τ plus d. A fundamental question about any complexity measure is whether or not it is subadditive. In this paper we resolve this question for process complexity by proving that neither of these process complexities is subadditive.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Process and truth-table characterisations of randomness
TL;DR: This paper uses quick process machines to provide characterisations of computable randomness, Schnorr randomness and weak randomness in terms of truth-table reducibility.
10
Strict process machine complexity
TL;DR: It is shown that for strict process machines, complexity of a sequence or of a subset of Cantor space is equal to its effective Hausdorff dimension.
2
Randomness and Computability
Adam R. Day
- 01 Jan 2011
TL;DR: The two approaches that have been used to define randomness on Cantor space for non-computable measures: that of Reimann and Slaman, along with the uniform test approach first introduced by Levin and also used by Gacs, Hoyrup and Rojas, are equivalent.
Related Papers (5)
Adam R. Day
- 01 Jan 2009
Eyal Kushilevitz,Enav Weinreb +1 more
- 31 May 2009
Erez Petrank,Gábor Tardos +1 more