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## WHAT IS IT?
This program models a twodimensional cellular automaton. This particular cellular automaton is called Day and Night.
Cellular automata (CA) were invented in the 1940s by Stanislaw Ulam and John von Neumann to prove that selfreproduction is possible in machines and to further link biology and compuatation.
A CA is a collection of cells arranged in a grid, such that each cell changes state as a function of time according to a defined set of rules that includes the states of neighboring cells. In other words, a cellular automaton can thought of as computational machine performing actions based on specified rules. These are idealized models of complex systems as they consist of large network of simple components with limited communication among components and no central control. Cellular automata result complex dynamics from simple rules.
The rule modeled here is given the name "Day & Night" because both its states states are symmetric meaning if all states are switched if on, turn off vise versa the automata will proceed in the same manner.
As with Conway ’s Life the automaton model here displays Class IV Behavior. Although the day and night rule set is classified as a chaotic cellular automaton, it behaves very differently from Conway's original rules because of its unique properties.
## HOW IT WORKS
The day and night rule set is as follows. Each cell checks the state of itself and its eight surrounding neighbors and then sets itself to either alive or dead. If there are less than two alive neighbors, then the cell dies. In this cellular automaton, a living cell survives if it has 3, 4, 6, 7, or 8 neighbors and a dead cell becomes alive when it has 3, 6, 7, or 8 neighbors (otherwise, a cell remains in the same state). This is done in parallel and continues forever.
## HOW TO USE IT
The INITIALDENSITY slider determines the initial density of cells that are alive.
## THINGS TO NOTICE
Find stable shapes that are motionless. Also, notice any recurring shapes.
Observe how the population dynamics changes in each intialization and the how quickly each leads to a different stable point.
Notice how the chaotic structures gradually consdilate into large regions of living and dead cells with constantly shifting boundaries with activity which mirrors the behaviour of other regions.
Observe how the intensity of living cells affect the population dynamics in any particular simulation. Compare the same to Conway's orginal rule set. Do intializations stablize relatively quickly?
View the PERCENTAGE CURRENT DENSITY monitor to see the current value of density of living cells.
## THINGS TO TRY
Is it possible for this cellular automata to be used to compute anything? How?
Try to build various objects which don't die (using DRAWCELLS).
Try to change the shape of grid and see how it affects the steady state as well as the time to reach it.
## EXTENDING THE MODEL
Modify the rules of the model to simulate different complex behaviours and observe the resulting character of a given rule set.
## CREDITS
The author would like to acknowledge Mr. Rinkaj Goyal, USICT for his guidance and support which has been immense help in understanding the fundamentals of Netlogo and complex systems as well as provided motivation to carry out authentic and valuable research.
## REFERENCES
email: abhigenie92@gmail.com<mailto:abhigenie92@gmail.com>
Day & Night was invented and named by Nathan Thompson in 1997, and later explored and discussed by David I. Bell.
Bell, David I. (1997), Day & Night  An Interesting Variant of Life
Life model in Netlogo library was particularly helpful for reference.

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