From Data and Signals Cellular Automata to Self-organizing Circuits

Author(s):  
André Stauffer ◽  
Joël Rossier
2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Takeshi Ishida

We propose a new algorithm to build self-organizing and self-repairing marine structures on the ocean floor, where humans and remotely operated robots cannot operate. The proposed algorithm is based on the one-dimensional cellular automata model and uses simple transition rules to produce various complex patterns. This cellular automata model can produce various complex patterns like sea shells with simple transition rules. The model can simulate the marine structure construction process with distributed cooperation control instead of central control. Like living organism is constructed with module called cell, we assume that the self-organized structure consists of unified modules (structural units). The units pile up at the bottom of the sea and a structure with the appropriate shape eventually emerges. Using the attribute of emerging patterns in the one-dimensional cellular automata model, we construct specific structures based on the local interaction of transition rules without using complex algorithms. Furthermore, the model requires smaller communication data among the units because it only relies on communication between adjacent structural units. With the proposed algorithm, in the future, it will be possible to use self-assembling structural modules without complex built-in computers.


2006 ◽  
Author(s):  
Dianxun Shuai ◽  
Qing Shuai ◽  
Liangjun Huang ◽  
Yuzhe Liu ◽  
Yuming Dong

1998 ◽  
Vol 2 (2) ◽  
pp. 111-125 ◽  
Author(s):  
Roger White

Cellular automata provide a high-resolution representation of urban spatial dynamics.Consequently they give the most realistic predictions of urban structural evolution, and in particular they are able to replicate the various fractal dimensionalities of actual cities. However, since these models do not readily incorporate certain phenomena like density measures and long-distance (as opposed to neighbourhood) spatial interactions, their performance may be enhanced by integrating them with other types of urban models.Cellular automata based models promise deeper theoretical insights into the nature of cities as self-organizing structures.


Author(s):  
Yusuke Iwase ◽  
Reiji Suzuki ◽  
Takaya Arita

Cellular Automata (CAs) have been investigated extensively as abstract models of the decentralized systems composed of autonomous entities characterized by local interactions. However, it is poorly understood how CAs can interact with their external environment, which would be useful for implementing decentralized pervasive systems that consist of billions of components (nodes, sensors, etc.) distributed in our everyday environments. This chapter focuses on the emergent properties of CAs induced by external perturbations toward controlling decentralized pervasive systems. We assumed a minimum task in which a CA has to change its global state drastically after every occurrence of a perturbation period. In the perturbation period, each cell state is modified by using an external rule with a small probability. By conducting evolutionary searches for rules of CAs, we obtained interesting behaviors of CAs in which their global state cyclically transited among different stable states in either ascending or descending order. The self-organizing behaviors are due to the clusters of cell states that dynamically grow through occurrences of perturbation periods. These results imply that we can dynamically control the global behaviors of decentralized systems by states of randomly selected components only.


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