Abstract
The basic rules of self-organization using a totalistic cellular automaton (CA) were investigated, for which the cell state was determined by summing the states of neighboring cells, like in Conway’s Game of Life. This study used a short-range and long-range summation of the cell states around the focal cell. These resemble reaction-diffusion (RD) equations, in which self-organizing behavior emerges from interactions between an activating factor and an inhibiting factor. In addition, Game-of-Life-type rules, in which a cell cannot survive when adjoined by too many or too few living cells, were applied. Our model was able to mimic patterns characteristic of biological cells, including movement, growth, and reproduction. This result suggests the possibility of controlling self-organized patterns. Our model can also be applied to the control of engineering systems, such as multirobot swarms and self-assembling microrobots.
Highlights
Self-organization phenomena, in which global structures are produced from purely local interactions, are found in fields ranging from biology to human societies
The patterns became increasingly unstable over the calculation field, and this instability increased the rate of pattern emergence, including self-reproducing spot patterns and stripe patterns
To a totalistic cellular automaton (CA) model with an activating inner area and inhibiting outer area. This is a CA model, yet a totalistic CA model with an activating inner area and inhibiting outer area. This is a CA model, it works in a way that is equivalent to that of RD approaches like the Turing pattern model
Summary
Self-organization phenomena, in which global structures are produced from purely local interactions, are found in fields ranging from biology to human societies. If these emergent processes were to be controlled, various applications would be possible in engineering fields. For this purpose, the conditions under which they emerge must be elucidated. The conditions under which they emerge must be elucidated This is one of the goals of the study of complex systems. Such control methods may allow the automatic construction of machines. The methods allow for the growth of artificial organs or the support of ecosystem conservation, as well as clarifying the emergence of the first life on ancient earth
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