acss.data-package {acss.data} | R Documentation

## Data Only: Algorithmic Complexity of Short Strings (Computed via Coding Theorem Method)

### Description

Data only package providing the algorithmic complexity of short strings, computed using the coding theorem method. For a given set of symbols in a string, all possible or a large number of random samples of Turing machines (TM) with a given number of states (e.g., 5) and number of symbols corresponding to the number of symbols in the strings were simulated until they reached a halting state or failed to end. This package contains data on 4.5 million strings from length 1 to 12 simulated on TMs with 2, 4, 5, 6, and 9 symbols. The complexity of the string corresponds to the distribution of the halting states of the TMs.

### Details

Package: | acss.data
Type: | Package
Version: | 1.0
Date: | 2013-04-02
License: GPL (>= 2)
URL: | http://complexitycalculator.com/methodology.html

This package only contains data. Therefore, this package is not intended to be used directly, but through functions in package acss.

### Author(s)

The data in this package was created by Fernando Soler Toscano, Nicolas Gauvrit, and Hector Zenil.
Data was ported to R by Henrik Singmann.

Maintainer: Henrik Singmann <singmann@gmail.com>

### References

Delahaye, J.-P., & Zenil, H. (2012). Numerical evaluation of algorithmic complexity for short strings: A glance into the innermost structure of randomness. Applied Mathematics and Computation, 219(1), 63-77. doi:10.1016/j.amc.2011.10.006

Gauvrit, N., Zenil, H., Delahaye, J.-P., & Soler-Toscano, F. (2014). Algorithmic complexity for short binary strings applied to psychology: a primer. Behavior Research Methods. doi:10.3758/s13428-013-0416-0

Soler-Toscano, F., Zenil, H., Delahaye, J.-P., & Gauvrit, N. (2012). Calculating Kolmogorov Complexity from the Output Frequency Distributions of Small Turing Machines. arXiv:1211.1302 [cs.it].

### See Also

package acss for functions accessing this data.

[Package acss.data version 1.0 Index]