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What does the informational complexity of dynamical networked systems tell us about intrinsic mechanisms and functions of these complex systems? Recent complexity measures such as integrated information have sought to operationalize this…

Neural and Evolutionary Computing · Computer Science 2017-07-06 Xerxes D. Arsiwalla , Pedro A. M. Mediano , Paul F. M. J. Verschure

Building software-driven systems that are easily understood becomes a challenge, with their ever-increasing complexity and autonomy. Accordingly, recent research efforts strive to aid in designing explainable systems. Nevertheless, a common…

Artificial Intelligence · Computer Science 2019-02-11 Dimitri Bohlender , Maximilian A. Köhl

Integrated information theory (IIT) starts from consciousness itself and identifies a set of properties (axioms) that are true of every conceivable experience. The axioms are translated into a set of postulates about the substrate of…

Nature can be seen as informational structure with computational dynamics (info-computationalism), where an (info-computational) agent is needed for the potential information of the world to actualize. Starting from the definition of…

Artificial Intelligence · Computer Science 2013-11-05 Gordana Dodig-Crnkovic

This article is a short introduction to generic case complexity, which is a recently developed way of measuring the difficulty of a computational problem while ignoring atypical behavior on a small set of inputs. Generic case complexity…

Computational Complexity · Computer Science 2007-07-11 Robert Gilman , Alexei G. Miasnikov , Alexey D. Myasnikov , Alexander Ushakov

A general condition determining the optimal performance of a complex system has not yet been found and the possibility of its existence is unknown. To contribute in this direction, an optimization algorithm as a complex system is presented.…

Computational Complexity · Computer Science 2007-05-23 Victor Korotkikh , Galina Korotkikh , Darryl Bond

Effective complexity measures the information content of the regularities of an object. It has been introduced by M. Gell-Mann and S. Lloyd to avoid some of the disadvantages of Kolmogorov complexity, also known as algorithmic information…

Information Theory · Computer Science 2010-11-22 Nihat Ay , Markus Mueller , Arleta Szkola

Quantum complexity measures the difficulty of realizing a quantum process, such as preparing a state or implementing a unitary. We present an approach to quantifying the thermodynamic resources required to implement a process if the…

The idea is advanced that self-organization in complex systems can be treated as decision making (as it is performed by humans) and, vice versa, decision making is nothing but a kind of self-organization in the decision maker nervous…

Adaptation and Self-Organizing Systems · Physics 2014-08-08 V. I. Yukalov , D. Sornette

Several approaches and corresponding definitions of complexity have been developed in different fields. Urban systems are the archetype of complex socio-technical systems concerned with these different viewpoints. We suggest in this chapter…

Computers and Society · Computer Science 2020-01-09 Juste Raimbault

The global availability of communication services makes it possible to interconnect independently developed systems, called constituent systems, to provide new synergistic services and more efficient economic processes. The characteristics…

Software Engineering · Computer Science 2013-11-15 Hermann Kopetz

Complexity measures in the context of the Integrated Information Theory of consciousness try to quantify the strength of the causal connections between different neurons. This is done by minimizing the KL-divergence between a full system…

Methodology · Statistics 2021-02-09 Carlotta Langer , Nihat Ay

In this work we give a concise definition of information loss from a system-theoretic point of view. Based on this definition, we analyze the information loss in static input-output systems subject to a continuous-valued input. For a…

Information Theory · Computer Science 2012-04-02 Bernhard C. Geiger , Gernot Kubin

It is a challenge to manage complex systems efficiently without confronting NP-hard problems. To address the situation we suggest to use self-organization processes of prime integer relations for information processing. Self-organization…

Computational Complexity · Computer Science 2007-10-23 Victor Korotkikh , Galina Korotkikh

How much information do large brain networks integrate as a whole over the sum of their parts? Can the dynamical complexity of such networks be globally quantified in an information-theoretic way and be meaningfully coupled to brain…

Neurons and Cognition · Quantitative Biology 2016-12-22 Xerxes D. Arsiwalla , Paul Verschure

For a computational system to be intelligent, it should be able to perform, at least, basic deductions. Nonetheless, since deductions are, in some sense, equivalent to tautologies, it seems that they do not provide new information. The…

Logic in Computer Science · Computer Science 2014-04-21 Anderson de Araújo

We consider biological individuality in terms of information theoretic and graphical principles. Our purpose is to extract through an algorithmic decomposition system-environment boundaries supporting individuality. We infer or detect…

Populations and Evolution · Quantitative Biology 2014-12-09 David Krakauer , Nils Bertschinger , Eckehard Olbrich , Nihat Ay , Jessica C. Flack

Complexity of patterns is a key information for human brain to differ objects of about the same size and shape. Like other innate human senses, the complexity perception cannot be easily quantified. We propose a transparent and universal…

Pattern Formation and Solitons · Physics 2020-12-30 Andrey A. Bagrov , Ilia A. Iakovlev , Askar A. Iliasov , Mikhail I. Katsnelson , Vladimir V. Mazurenko

In this paper, we revisit a central concept in Kolmogorov complexity in which one would equate program-size complexity with information content. Despite the fact that Kolmogorov complexity has been widely accepted as an objective measure of…

Information Theory · Computer Science 2017-10-19 Fouad B. Chedid

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying…

Neurons and Cognition · Quantitative Biology 2015-01-09 Robin A. A. Ince , Simon R. Schultz , Stefano Panzeri
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