Ruliology is a fascinating area of study introduced by Stephen Wolfram that focuses on how simple rules can lead to complex outcomes. It makes us think about the big questions in life, especially when we look at examples like Conway's Game of Life. This game is more than just a fun computer simulation; it's a tool that helps us understand deep philosophical concepts.
Conway's Game of Life: A Simple Model with Big Ideas
The Game of Life is played on a grid where cells turn on (living) or off (dead) based on a few simple rules:
1. Any live cell with fewer than two live neighbors dies, as if caused by underpopulation.
2. Any live cell with two or three live neighbors lives on to the next generation.
3. Any live cell with more than three live neighbors dies, as if caused by overpopulation.
4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction
How the rules in Conway's Game of Life are laid out visually
Image source: Hirose, Takayuki & Sawaragi, Tetsuo. (2020). Extended FRAM model based on cellular automaton to clarify complexity of socio-technical systems and improve their safety. Safety Science. 123. 104556. 10.1016/j.ssci.2019.104556.
Despite these straightforward rules, the game can create highly complex patterns that almost seem alive. This raises some interesting questions: If simple instructions can create complex, lifelike patterns, what does this tell us about the universe's rules?
What Ruliology Tells Us About the World
Ruliology asks us to think about whether the complex things we see around us, like weather patterns or the structure of living cells, are the result of simple underlying rules. This idea changes our view from just looking at what things are to thinking about how they behave based on these rules.
Free Will and Determinism
The Game of Life shows that everything that happens is predictable and follows specific rules. This might make us think everything is predetermined. However, the unpredictable patterns that emerge challenge our thoughts about free will and fate. Could our universe work the same way, with all its complexity coming from simple, predictable rules?
Life and Existence
The Game of Life also makes us question what it means to be alive. The patterns in the game act like they're alive because they grow, reproduce, and die. This blurs the line between what's real and what's artificial, leading us to wonder: What does it really mean to be alive? Is it about the materials something is made of or how it behaves?
A video on the complex patterns resulting from Conway's Game of Life
Video source: Awesome Computer, director. Best of Conway's game of life. 2018. Youtube, https://www.youtube.com/watch?v=Gbvy6gY5Ev4&ab_channel=AwesomeComputer.
Chaos and Order
Through ruliology and cellular automata like the Game of Life, we see how fixed rules can create dynamic, seemingly chaotic systems. This reflects the philosophical debate about the universe: Is it naturally chaotic and shaped into order by laws, or does order naturally emerge from chaos?
Ruliology's Broader Impact
Ruliology doesn't just teach us about science; it also deepens our understanding of life's big questions. By studying simple rules in systems like the Game of Life, we learn about the complexities of the world and reflect on the philosophical issues of existence and consciousness. Ruliology bridges science and philosophy, helping us see the patterns of order and chaos that shape our world.
This summer, I had the incredible opportunity to attend the Wolfram High School Summer Research Program. Interested in ruliology, I focused my project on mobile automata, a type of simple program similar to cellular automata. Mobile Automata with Non-Local Rules In cellular automata, all cells update in parallel according to a set of rules, whereas mobile automata feature a single active cell that updates at each iteration. The rules for mobile automata dictate the new state of the active cell and its movement. These rules consider the states of the active cell and its immediate neighbors, determining the new color of the active cell and whether it moves to the left or right. Traditionally, mobile automata involve the active cell interacting with its immediate left and right neighbors. However, in my project, I explored the effects of non-local interactions, where the dependent cells are farther away from the active cell. For instance, I examined scenarios where the dependent cells wer
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