BIRS Lab 1


Wolfram’s findings in “A New Kind of Science” arrived at a very crucial point; that simple programs have the ability and potential to produce complex, irregular behaviors. He came to this finding, known as Rule 30, through his experiments on generating patterns from providing the computer with a set of simple rules, or cellular automata. An interesting application of cellular automata would be modeling simulations of forest fires, which was explored in a 2018 study (Rui et al). Combining cellular automata and previous forest fire simulation models allows one to map out the spatiotemporal impact of a forest fire, and if reversed, trace the root locations of a fire.


Code Examples

  1. Simple Cellular Automaton (Python)

  1. Multiplexed 2D Cellular Automata (Scratch MIT)

  1. Rock-Paper-Scissors Cellular Automata (Scratch MIT)


I modified the Rock-Paper-Scissors Cellular Automata created on Scratch MIT. The rules of the cellular automaton were according to color, (paper = green, scissors = blue, rock = purple) and the frequency of the dots were according to the delay that we could adjust. I played around with it and created different colorful patterns, after which I then decided to switch the rules. I changed the colors corresponding to rock, paper, and scissors respectively. This yielded the same results as the original project, but with different colors.



I found that cellular automata are very much like early adaptations of computer programs mimicking living organisms. Like the cellular automata examples shown, living organisms are based on very simple rules and need very little to survive but evolve into irregular, complex beings. I thought Scratch MIT was a good introduction to tinkering, and I enjoyed making variations of the cellular automaton.