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.

Game Theory Cancer Models of Cancer Cell-Stromal Cell Dynamics using Interacting Particle Systems

2020 ◽  
Vol 15 (03) ◽  
pp. 171-193
Author(s):  
Yinan Zheng ◽  
Yusha Sun ◽  
Gonzalo Torga ◽  
Kenneth Pienta ◽  
Robert Austin
Keyword(s):  
Game Theory ◽  
Interacting Particle Systems ◽  
Evolutionary Game ◽  
Mean Field ◽  
Theory Model ◽  
Particle Systems ◽  
Cell Dynamics ◽  
Field Approach ◽  
Interacting Particle ◽  
The Mean

We describe an evolutionary game theory model that has been used to predict the population dynamics of interacting cancer and stromal cells. We first consider the mean field case assuming homogeneous and nondiscrete populations. Interacting Particle Systems (IPS) are then presented as a discrete and spatial alternative to the mean field approach. Finally, we discuss cases where IPS gives results different from the mean field approach.

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 Condensation of SIP Particles and Sticky Brownian Motion

2021 ◽  
Vol 183 (3) ◽  
Author(s):  
Mario Ayala ◽  
Gioia Carinci ◽  
Frank Redig
Keyword(s):  
Brownian Motion ◽  
Interacting Particle Systems ◽  
Particle Systems ◽  
Self Duality ◽  
Inclusion Process ◽  
Interacting Particle ◽  
New Information ◽  
Homogeneous Product ◽  
Coarsening Dynamics ◽  
The Difference

AbstractWe study the symmetric inclusion process (SIP) in the condensation regime. We obtain an explicit scaling for the variance of the density field in this regime, when initially started from a homogeneous product measure. This provides relevant new information on the coarsening dynamics of condensing interacting particle systems on the infinite lattice. We obtain our result by proving convergence to sticky Brownian motion for the difference of positions of two SIP particles in the sense of Mosco convergence of Dirichlet forms. Our approach implies the convergence of the probabilities of two SIP particles to be together at time t. This, combined with self-duality, allows us to obtain the explicit scaling for the variance of the fluctuation field.

scholarly journals Cognitive Profiling of Nodes in 6G through Multiplex Social Network and Evolutionary Collective Dynamics

2021 ◽  
Vol 13 (5) ◽  
pp. 135
Author(s):  
Marialisa Scatá ◽  
Barbara Attanasio ◽  
Aurelio La Corte
Keyword(s):  
Social Network ◽  
Complex Systems ◽  
Communication Networks ◽  
Digital Health ◽  
Evolutionary Game ◽  
Mathematical Representation ◽  
Collective Dynamics ◽  
Self Organized ◽  
Learning And Cognition ◽  
Application Fields

Complex systems are fully described by the connectedness of their elements studying how these develop a collective behavior, interacting with each other following their inner features, and the structure and dynamics of the entire system. The forthcoming 6G will attempt to rewrite the communication networks’ perspective, focusing on a radical revolution in the way entities and technologies are conceived, integrated and used. This will lead to innovative approaches with the aim of providing new directions to deal with future network challenges posed by the upcoming 6G, thus the complex systems could become an enabling set of tools and methods to design a self-organized, resilient and cognitive network, suitable for many application fields, such as digital health or smart city living scenarios. Here, we propose a complex profiling approach of heterogeneous nodes belonging to the network with the goal of including the multiplex social network as a mathematical representation that enables us to consider multiple types of interactions, the collective dynamics of diffusion and competition, through social contagion and evolutionary game theory, and the mesoscale organization in communities to drive learning and cognition. Through a framework, we detail the step by step modeling approach and show and discuss our findings, applying it to a real dataset, by demonstrating how the proposed model allows us to detect deeply complex knowable roles of nodes.

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