Emergence of Turing Patterns in a Simple Cellular Automata-Like Model via Exchange of Integer Values between Adjacent Cells
The Turing pattern model is one of the theories used to describe organism formation patterns. Using this model, self-organized patterns emerge due to differences in the concentrations of activators and inhibitors. Here a cellular automata (CA)-like model was constructed wherein the Turing patterns e...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2020/2308074 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832568169713106944 |
|---|---|
| author | Takeshi Ishida |
| author_facet | Takeshi Ishida |
| author_sort | Takeshi Ishida |
| collection | DOAJ |
| description | The Turing pattern model is one of the theories used to describe organism formation patterns. Using this model, self-organized patterns emerge due to differences in the concentrations of activators and inhibitors. Here a cellular automata (CA)-like model was constructed wherein the Turing patterns emerged via the exchange of integer values between adjacent cells. In this simple hexagonal grid model, each cell state changed according to information exchanged from the six adjacent cells. The distinguishing characteristic of this model is that it presents a different pattern formation mechanism using only one kind of token, such as a chemical agent that ages via spatial diffusion. Using this CA-like model, various Turing-like patterns (spots or stripes) emerge when changing two of four parameters. This model has the ability to support Turing instability that propagates in the neighborhood space; global patterns are observed to spread from locally limited patterns. This model is not a substitute for a conventional Turing model but rather is a simplified Turing model. Using this model, it is possible to control the formation of multiple robots into such forms as circle groups or dividing a circle group into two groups, for example. In the field of information networks, the presented model could be applied to groups of Internet-of-Things devices to create macroscopic spatial structures to control data traffic. |
| format | Article |
| id | doaj-art-c697ac3cab6f40018fae6e0725b8ac94 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-c697ac3cab6f40018fae6e0725b8ac942025-02-03T00:59:43ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2020-01-01202010.1155/2020/23080742308074Emergence of Turing Patterns in a Simple Cellular Automata-Like Model via Exchange of Integer Values between Adjacent CellsTakeshi Ishida0Department of Ocean Mechanical Engineering, National Fisheries University, Shimonoseki, Yamaguchi, JapanThe Turing pattern model is one of the theories used to describe organism formation patterns. Using this model, self-organized patterns emerge due to differences in the concentrations of activators and inhibitors. Here a cellular automata (CA)-like model was constructed wherein the Turing patterns emerged via the exchange of integer values between adjacent cells. In this simple hexagonal grid model, each cell state changed according to information exchanged from the six adjacent cells. The distinguishing characteristic of this model is that it presents a different pattern formation mechanism using only one kind of token, such as a chemical agent that ages via spatial diffusion. Using this CA-like model, various Turing-like patterns (spots or stripes) emerge when changing two of four parameters. This model has the ability to support Turing instability that propagates in the neighborhood space; global patterns are observed to spread from locally limited patterns. This model is not a substitute for a conventional Turing model but rather is a simplified Turing model. Using this model, it is possible to control the formation of multiple robots into such forms as circle groups or dividing a circle group into two groups, for example. In the field of information networks, the presented model could be applied to groups of Internet-of-Things devices to create macroscopic spatial structures to control data traffic.http://dx.doi.org/10.1155/2020/2308074 |
| spellingShingle | Takeshi Ishida Emergence of Turing Patterns in a Simple Cellular Automata-Like Model via Exchange of Integer Values between Adjacent Cells Discrete Dynamics in Nature and Society |
| title | Emergence of Turing Patterns in a Simple Cellular Automata-Like Model via Exchange of Integer Values between Adjacent Cells |
| title_full | Emergence of Turing Patterns in a Simple Cellular Automata-Like Model via Exchange of Integer Values between Adjacent Cells |
| title_fullStr | Emergence of Turing Patterns in a Simple Cellular Automata-Like Model via Exchange of Integer Values between Adjacent Cells |
| title_full_unstemmed | Emergence of Turing Patterns in a Simple Cellular Automata-Like Model via Exchange of Integer Values between Adjacent Cells |
| title_short | Emergence of Turing Patterns in a Simple Cellular Automata-Like Model via Exchange of Integer Values between Adjacent Cells |
| title_sort | emergence of turing patterns in a simple cellular automata like model via exchange of integer values between adjacent cells |
| url | http://dx.doi.org/10.1155/2020/2308074 |
| work_keys_str_mv | AT takeshiishida emergenceofturingpatternsinasimplecellularautomatalikemodelviaexchangeofintegervaluesbetweenadjacentcells |