scholarly journals A Five Species Cyclically Dominant Evolutionary Game with Fixed Direction: A New Way to Produce Self-Organized Spatial Patterns

Entropy ◽  
2016 ◽  
Vol 18 (8) ◽  
pp. 284 ◽  
Author(s):  
Yibin Kang ◽  
Qiuhui Pan ◽  
Xueting Wang ◽  
Mingfeng He
Keyword(s):  
Spatial Patterns ◽  
Evolutionary Game ◽  
Self Organized ◽  
Fixed Direction

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.

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.

scholarly journals Exogenous disturbances and endogenous self-organized processes are not mutually exclusive drivers of spatial patterns in macroalgal assemblages

2020 ◽  
Author(s):  
J. He ◽  
L. Rindi ◽  
C. Mintrone ◽  
L. Benedetti-Cecchi
Keyword(s):  
Spatial Patterns ◽  
Empirical Work ◽  
Power Laws ◽  
Local Scale ◽  
Species Assemblages ◽  
Spatial Gradient ◽  
Gap Size ◽  
Scale Interactions ◽  
Relative Contribution ◽  
Self Organized

AbstractComplex spatial patterns are common in coastal marine systems, but mechanisms underlying their formation are disputed. Most empirical work has focused on exogeneous spatially structured disturbances as the leading cause of pattern formation in species assemblages. However, theoretical and observational studies suggest that complex spatial patterns, such as power laws in gap-size distribution, may result from endogenous self-organized processes involving local-scale interactions. The lack of studies simultaneously assessing the influence of spatially variable disturbances and local-scale interactions has fuelled the idea that exogenous and endogenous processes are mutually exclusive explanations of spatial patterns in marine ecosystems. To assess the relative contribution of endogenous and exogenous processes in the emergence of spatial patterns, an intertidal assemblage of algae and invertebrates was exposed for 2 years to various combinations of intensity and spatial patterns of disturbance. Localized disturbances impinging at the margins of previously disturbed clearings and homogenous disturbances without any spatial pattern generated heterogeneous distributions of disturbed gaps and macroalgal patches, characterized by a truncated or a pure power-law scaling. Spatially varying disturbances produced a spatial gradient in the distribution of algal patches and, to a lesser extent, also a power-scaling in both patch- and gap-size distributions. These results suggest that exogenous and endogenous processes are not mutually exclusive forces that can lead to the formation of similar spatial patterns in species assemblages.

scholarly journals Phase separation explains a new class of self-organized spatial patterns in ecological systems

2013 ◽  
Vol 110 (29) ◽  
pp. 11905-11910 ◽  
Author(s):  
Q.-X. Liu ◽  
A. Doelman ◽  
V. Rottschafer ◽  
M. de Jager ◽  
P. M. J. Herman ◽  
...  
Keyword(s):  
Phase Separation ◽  
Spatial Patterns ◽  
Ecological Systems ◽  
New Class ◽  
Self Organized

Self-organized spatial patterns of vegetation in alpine grasslands

2007 ◽  
Vol 201 (2) ◽  
pp. 233-242 ◽  
Author(s):  
C.L. Alados ◽  
A. El Aich ◽  
B. Komac ◽  
Y. Pueyo ◽  
R. García-Gonzalez
Keyword(s):  
Spatial Patterns ◽  
Alpine Grasslands ◽  
Self Organized
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