14 papers · ranked by Valyu relevance
Frank Emmert-Streib, Enrico Scalas
Background The evaluation of the complexity of an observed object is an old but outstanding problem. In this paper we are tying on this problem introducing a measure called statistic complexity. Methodology/Principal Findings This complexity measure is different to all other measures in the following senses. First, it…
Catalina Morales-Rojas, Ronney B. Panerai, José Luis Jara, Maria Rubega + 2 more
'Maria Rubega' 'Roberto Di Marco' 'Emanuela Formaggio'] The brain is a fundamental organ for the human body to function properly, for which it needs to receive a continuous flow of blood, which explains the existence of control mechanisms that act to maintain this flow as constant as possible in a process known as…
Marcos G. Alpino, Tiago Debarba, Reinaldo O. Vianna, André T. Cesário + 1 more
'André T. Cesário' 'Viktor Dodonov'] We investigate the role of a statistical complexity measure to assign equilibration in isolated quantum systems. While unitary dynamics preserve global purity, expectation values of observables often exhibit equilibration-like behavior, raising the question of whether a measure of…
André T. Cesário, Diego L. B. Ferreira, Tiago Debarba, Fernando Iemini + 3 more
'Fernando Iemini' 'Thiago O. Maciel' 'Reinaldo O. Vianna' 'Antonio Vidiella-Barrranco'] We introduce a quantum version for the statistical complexity measure, in the context of quantum information theory, and use it as a signaling function of quantum order-disorder transitions. We discuss the possibility for such…
Jorge M. Silva, Eduardo Pinho, Sérgio Matos, Diogo Pratas
Sources that generate symbolic sequences with algorithmic nature may differ in statistical complexity because they create structures that follow algorithmic schemes, rather than generating symbols from a probabilistic function assuming independence. In the case of Turing machines, this means that machines with the same…
George Datseris, Kristian Agasøster Haaga, Alessandro Mengarelli
In the nonlinear timeseries analysis literature, countless quantities have been presented as new “entropy” or “complexity” measures, often with similar roles. The ever-increasing pool of such measures makes creating a sustainable and all-encompassing software for them difficult both conceptually and pragmatically. Such…
David P. Feldman, James P. Crutchfield, Antonio M. Scarfone
We compare and contrast three different, but complementary views of “structure” and “pattern” in spatial processes. For definiteness and analytical clarity, we apply all three approaches to the simplest class of spatial processes: one-dimensional Ising spin systems with finite-range interactions. These noncritical…
Kamal Dingle, Mohammad Alaskandarani, Boumediene Hamzi, Ard A. Louis + 1 more
Arguments inspired by algorithmic information theory predict an inverse relation between the probability and complexity of output patterns in a wide range of input-output maps. This phenomenon is known as simplicity bias. By viewing the parameters of dynamical systems as inputs, and the resulting (digitised)…
Jarosław Klamut, Ryszard Kutner, Zbigniew R. Struzik
Recently, it has been argued that entropy can be a direct measure of complexity, where the smaller value of entropy indicates lower system complexity, while its larger value indicates higher system complexity. We dispute this view and propose a universal measure of complexity that is based on Gell-Mann’s view of…
Hector Zenil
Some established and also novel techniques in the field of applications of algorithmic (Kolmogorov) complexity currently co-exist for the first time and are here reviewed, ranging from dominant ones such as statistical lossless compression to newer approaches that advance, complement and also pose new challenges and…
Hector Zenil, James A. R. Marshall, Jesper Tegnér
Being able to objectively characterize the intrinsic complexity of behavioral patterns resulting from human or animal decisions is fundamental for deconvolving cognition and designing autonomous artificial intelligence systems. Yet complexity is difficult in practice, particularly when strings are short. By numerically…
Hector Zenil, Narsis A. Kiani, Jesper Tegnér
Information-theoretic-based measures have been useful in quantifying network complexity. Here we briefly survey and contrast (algorithmic) information-theoretic methods which have been used to characterize graphs and networks. We illustrate the strengths and limitations of Shannon’s entropy, lossless compressibility…
Alexander F. Siegenfeld, Yaneer Bar-Yam, António Lopes
Ashby’s law of requisite variety allows a comparison of systems with their environments, providing a necessary (but not sufficient) condition for system efficacy: A system must possess at least as much complexity as any set of environmental behaviors that require distinct responses from the system. However, to account…
Tim Angelike, Jochen Musch
Whether and how well people can behave randomly is of interest in many areas of psychological research. The ability to generate randomness is often investigated using random number generation (RNG) tasks, in which participants are asked to generate a sequence of numbers that is as random as possible. However, there is…