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This video is NOT: - A life form - A particle simulation - An agent-based model - A physics engine It's a 'Selective' Multiple Neighborhood #CellularAutomata (#MNCA) pattern, run on a RX 6800XT GPU in #VulkanAutomata. A bit different to Conway's #GameOfLife, huh? 😁

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Wow. I've never seen anything quite like this, even though it feels familiar (like the things you clarified it wasn't)

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It's pretty cool weird how CA can emulate or resemble so many different systems at different scales! I did a 'light' writeup about simple #MNCA methods that might clarify or explain a bit about the why and how these patterns behave this way:

slackermanz.com

Understanding Multiple Neighborhood Cellular Automata - Slackermanz

Multiple Neighborhood Cellular Automata (MNCA) produce complex and robust emergent structures not commonly seen in simpler models

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Ty for this!

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I spent much of my 30s trying to figure this stuff out under a rock in a cave, figuratively speaking - bravo! Really appreciate the examples & write ups

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Thanks! If you have any questions or anything like that, I'm happy to discuss 🙂

Larkin

@Larkin

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@slackermanz

In follow up after reading with a fresh eye this morning, so do you compute the next state of a given cell for each neighborhood structure in a fixed sequence (e.g. nh1 > nh2 > nh3 ) or do you take an average among these nh evaluations in parallel to compute the next state?

3:05 PM · Jan 4, 2022Twitter Web App

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The neighborhood totals are calculated first, and the results are stored in variables. Those results can then be accessed in any order when performing the conditional updates. These are assessed in order of operations - overwriting (Discrete-State) or summing (Continuous-State)