Analysis of a simple self-organizing process

1982 ◽  
Vol 44 (2) ◽  
pp. 135-140 ◽  
Author(s):  
Teuvo Kohonen
Keyword(s):  
Self Organizing ◽  
Organizing Process

Makerchain: A blockchain with chemical signature for self-organizing process in social manufacturing

2019 ◽  
Vol 234 ◽  
pp. 767-778 ◽  
Author(s):  
Jiewu Leng ◽  
Pingyu Jiang ◽  
Kailin Xu ◽  
Qiang Liu ◽  
J. Leon Zhao ◽  
...  
Keyword(s):  
Chemical Signature ◽  
Self Organizing ◽  
Organizing Process

Cognition as self–organizing process

1987 ◽  
Vol 10 (2) ◽  
pp. 183-183 ◽  
Author(s):  
Gerhard Werner
Keyword(s):  
Self Organizing ◽  
Organizing Process

On the self-organizing process of large scale shear flows

2013 ◽  
Vol 20 (9) ◽  
pp. 092306 ◽  
Author(s):  
Andrew P. L. Newton ◽  
Eun-jin Kim ◽  
Han-Li Liu
Keyword(s):  
Large Scale ◽  
Shear Flows ◽  
The Self ◽  
Scale Shear ◽  
Self Organizing ◽  
Organizing Process

scholarly journals Adaptive self-organization of Bali’s ancient rice terraces

2017 ◽  
Vol 114 (25) ◽  
pp. 6504-6509 ◽  
Author(s):  
J. Stephen Lansing ◽  
Stefan Thurner ◽  
Ning Ning Chung ◽  
Aurélie Coudurier-Curveur ◽  
Çağil Karakaş ◽  
...  
Keyword(s):  
Green Revolution ◽  
Evolutionary Game ◽  
Power Laws ◽  
Global Scale ◽  
Specific Power ◽  
Spatial Patterning ◽  
Water Shortages ◽  
Local Adaptations ◽  
Self Organizing ◽  
Organizing Process

Spatial patterning often occurs in ecosystems as a result of a self-organizing process caused by feedback between organisms and the physical environment. Here, we show that the spatial patterns observable in centuries-old Balinese rice terraces are also created by feedback between farmers’ decisions and the ecology of the paddies, which triggers a transition from local to global-scale control of water shortages and rice pests. We propose an evolutionary game, based on local farmers’ decisions that predicts specific power laws in spatial patterning that are also seen in a multispectral image analysis of Balinese rice terraces. The model shows how feedbacks between human decisions and ecosystem processes can evolve toward an optimal state in which total harvests are maximized and the system approaches Pareto optimality. It helps explain how multiscale cooperation from the community to the watershed scale could persist for centuries, and why the disruption of this self-organizing system by the Green Revolution caused chaos in irrigation and devastating losses from pests. The model shows that adaptation in a coupled human–natural system can trigger self-organized criticality (SOC). In previous exogenously driven SOC models, adaptation plays no role, and no optimization occurs. In contrast, adaptive SOC is a self-organizing process where local adaptations drive the system toward local and global optima.

scholarly journals A Neural Network Model of Self-Organizing Process in Group Formation

1991 ◽  
Vol 27 (Supplement) ◽  
pp. 114-115
Author(s):  
Shigekazu Ishihara ◽  
Keiko Hatamoto ◽  
Mitsuo Nagamachi ◽  
Yukihiro Matsubara
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Group Formation ◽  
Self Organizing ◽  
Organizing Process
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