Simple hierarchical systems: Stability, self-organized criticality, and catastrophic behavior

1997 ◽  
Vol 55 (6) ◽  
pp. 6397-6403 ◽  
Author(s):  
E. M. Blanter ◽  
M. G. Shnirman
Keyword(s):  
Hierarchical Systems ◽  
Self Organized ◽  
Self Organized Criticality

scholarly journals Record dynamics of evolving metastable systems: theory and applications

2021 ◽  
Vol 94 (1) ◽  
Author(s):  
Paolo Sibani ◽  
Stefan Boettcher ◽  
Henrik Jeldtoft Jensen
Keyword(s):  
Physical Aging ◽  
Complex Dynamics ◽  
Power Laws ◽  
Hierarchical Systems ◽  
Relaxation Effects ◽  
Self Organized ◽  
Rapid Changes ◽  
Continuous Time Random Walks ◽  
Self Organized Criticality ◽  
Metastable Systems

Abstract Record Dynamics (RD) deals with complex systems evolving through a sequence of metastable stages. These are macroscopically distinguishable and appear stationary, except for the sudden and rapid changes, called quakes, which induce the transitions from one stage to the next. This phenomenology is well known in physics as “physical aging”, but from the vantage point of RD, the evolution of a class of systems of physical, biological, and cultural origin is rooted in a hierarchically structured configuration space and can, therefore, be analyzed by similar statistical tools. This colloquium paper strives to present in a coherent fashion methods and ideas that have gradually evolved over time. To this end, it first describes the differences and similarities between RD and two widespread paradigms of complex dynamics, Self-Organized Criticality and Continuous Time Random Walks. It then outlines the Poissonian nature of records events in white noise time-series, and connects it to the statistics of quakes in metastable hierarchical systems, arguing that the relaxation effects of quakes can generally be described by power laws unrelated to criticality. Several different applications of RD have been developed over the years. Some of these are described, showing the basic RD hypothesis and how the log-time homogeneity of quake dynamics, can be empirically verified in a given context. The discussion summarizes the paper and briefly mentions applications not discussed in detail. Finally, the outlook points to possible improvements and to new areas of research where RD could be of use. Graphic Abstract

scholarly journals Managing Complexity in Socio-Economic Systems

2009 ◽  
Vol 17 (2) ◽  
pp. 423-438 ◽  
Author(s):  
Dirk Helbing
Keyword(s):  
Complex Systems ◽  
Driving Forces ◽  
Production Systems ◽  
Power Laws ◽  
Self Organization ◽  
Economic Systems ◽  
Hierarchical Systems ◽  
Cascading Effects ◽  
Self Organized ◽  
Self Organized Criticality

This contribution summarizes some typical features of complex systems such as non-linear interactions, chaotic dynamics, the ``butterfly effect’’, phase transitions, self-organized criticality, cascading effects, and power laws. These imply sometimes quite unexpected, counter-intuitive, or even paradoxical behaviors of socio-economic systems. A typical example is the faster-is-slower effect. Due to their tendency of self-organization, complex systems are often hard to control. Instead of trying to control their behavior, it would often be better to pursue the approach of guided self-organization, i.e. to use the driving forces of the system rather than to fight against them. This is illustrated by the example of hierarchical systems, which need to fulfill certain principles in order to be efficient and robust in an ever-changing environment. We also discuss the important role of fluctuations and heterogeneity for the adaptability, flexibility and robustness of complex systems. The presentation is enriched by a number of examples ranging from decision behavior up to production systems and disaster spreading.

Problem behavior in autism spectrum disorders: A paradigmatic self-organized perspective of network structures

2019 ◽  
Vol 42 ◽  
Author(s):  
Lucio Tonello ◽  
Luca Giacobbi ◽  
Alberto Pettenon ◽  
Alessandro Scuotto ◽  
Massimo Cocchi ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Problem Behaviors ◽  
Autism Spectrum ◽  
The Self ◽  
Network Structures ◽  
Self Organized ◽  
Critical Equilibrium ◽  
Self Organized Criticality ◽  
Acute Agitation ◽  
Spectrum Disorders

AbstractAutism spectrum disorder (ASD) subjects can present temporary behaviors of acute agitation and aggressiveness, named problem behaviors. They have been shown to be consistent with the self-organized criticality (SOC), a model wherein occasionally occurring “catastrophic events” are necessary in order to maintain a self-organized “critical equilibrium.” The SOC can represent the psychopathology network structures and additionally suggests that they can be considered as self-organized systems.

Self-Organized Criticality in the Autowave Model of Speciation

2020 ◽  
Vol 75 (5) ◽  
pp. 398-408
Author(s):  
A. Y. Garaeva ◽  
A. E. Sidorova ◽  
N. T. Levashova ◽  
V. A. Tverdislov
Keyword(s):  
Self Organized ◽  
Self Organized Criticality

Modeling Extinction

2003 ◽  
Author(s):  
M. E. J. Newman ◽  
R. G. Palmer
Keyword(s):  
Evolutionary Biology ◽  
Large Scale ◽  
Competitive Exclusion ◽  
Applied Mathematics ◽  
Santa Fe ◽  
New Approach ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Extinction Events ◽  
Mass Extinction Events

Developed after a meeting at the Santa Fe Institute on extinction modeling, this book comments critically on the various modeling approaches. In the last decade or so, scientists have started to examine a new approach to the patterns of evolution and extinction in the fossil record. This approach may be called "statistical paleontology," since it looks at large-scale patterns in the record and attempts to understand and model their average statistical features, rather than their detailed structure. Examples of the patterns these studies examine are the distribution of the sizes of mass extinction events over time, the distribution of species lifetimes, or the apparent increase in the number of species alive over the last half a billion years. In attempting to model these patterns, researchers have drawn on ideas not only from paleontology, but from evolutionary biology, ecology, physics, and applied mathematics, including fitness landscapes, competitive exclusion, interaction matrices, and self-organized criticality. A self-contained review of work in this field.

scholarly journals Self-Organized Criticality on Twitter: Phenomenological Theory and Empirical Investigation Based on Data Analysis Results

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Andrey Dmitriev ◽  
Victor Dmitriev ◽  
Stepan Balybin
Keyword(s):  
Time Series ◽  
Critical State ◽  
Empirical Investigation ◽  
Phenomenological Theory ◽  
Self Organization ◽  
Protest Movements ◽  
Self Organized ◽  
Self Organized Criticality ◽  
Stochastic Sources ◽  
Adiabatic Mode

Recently, there has been an increasing number of empirical evidence supporting the hypothesis that spread of avalanches of microposts on social networks, such as Twitter, is associated with some sociopolitical events. Typical examples of such events are political elections and protest movements. Inspired by this phenomenon, we built a phenomenological model that describes Twitter’s self-organization in a critical state. An external manifestation of this condition is the spread of avalanches of microposts on the network. The model is based on a fractional three-parameter self-organization scheme with stochastic sources. It is shown that the adiabatic mode of self-organization in a critical state is determined by the intensive coordinated action of a relatively small number of network users. To identify the critical states of the network and to verify the model, we have proposed a spectrum of three scaling indicators of the observed time series of microposts.

scholarly journals On the Complexities of Complex Economic Dynamics

1999 ◽  
Vol 13 (4) ◽  
pp. 169-192 ◽  
Author(s):  
J. Barkley Rosser
Keyword(s):  
Adaptive Learning ◽  
Rational Expectations ◽  
Interacting Particle Systems ◽  
Complexity Analysis ◽  
Evolutionary Game ◽  
Equilibrium Dynamics ◽  
Self Organized ◽  
Policy Debates ◽  
Interacting Particle ◽  
Self Organized Criticality

Complex economic nonlinear dynamics endogenously do not converge to a point, a limit cycle, or an explosion. Their study developed out of earlier studies of cybernetic, catastrophic, and chaotic systems. Complexity analysis stresses interactions among dispersed agents without a global controller, tangled hierarchies, adaptive learning, evolution, and novelty, and out-of-equilibrium dynamics. Complexity methods include interacting particle systems, self-organized criticality, and evolutionary game theory, to simulate artificial stock markets and other phenomena. Theoretically, bounded rationality replaces rational expectations. Complexity theory influences empirical methods and restructures policy debates.

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