https://github.com/qc20/digitalorganism
DigitalOrganism is an interactive, visually captivating cellular automaton simulation that explores the fascinating world of emergent patterns and complexity. This project, inspired by Multiple Neighborhood Cellular Automata.
https://github.com/qc20/digitalorganism
algorithmic-art celluar-automata computational-biology computational-design creative-coding digital-art emergent-behavior generative-art interactive-visualizations javascript mnca pattern-generation real-time-visualization visual-computing
Last synced: 3 months ago
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DigitalOrganism is an interactive, visually captivating cellular automaton simulation that explores the fascinating world of emergent patterns and complexity. This project, inspired by Multiple Neighborhood Cellular Automata.
- Host: GitHub
- URL: https://github.com/qc20/digitalorganism
- Owner: QC20
- License: mit
- Created: 2024-07-23T21:58:03.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-07-24T20:30:43.000Z (10 months ago)
- Last Synced: 2024-12-31T21:28:25.884Z (5 months ago)
- Topics: algorithmic-art, celluar-automata, computational-biology, computational-design, creative-coding, digital-art, emergent-behavior, generative-art, interactive-visualizations, javascript, mnca, pattern-generation, real-time-visualization, visual-computing
- Language: JavaScript
- Homepage: https://qc20.github.io/DigitalOrganism/
- Size: 577 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# DigitalOrganism
DigitalOrganism is an interactive, visually captivating cellular automaton simulation that explores the fascinating world of emergent patterns and complexity. This project, inspired by Multiple Neighborhood Cellular Automata (MNCA), offers a unique playground for designers, researchers, and enthusiasts in the fields of generative art, computational design, and complex systems.
## Features
- Real-time cellular automaton simulation
- Interactive mouse-driven input
- Multiple rulesets for diverse pattern generation
- Customizable parameters for experimentation
## How It Works
DigitalOrganism uses a grid of cells that evolve based on the states of their neighbors. The simulation considers two neighborhoods for each cell:
1. A closer neighborhood (hood0)
2. A more extended neighborhood (hood1)
The evolution rules are defined by the `conditions` object, which determines the next state of each cell based on its current state and the states of its neighbors.
## Customization
The code is designed to be easily customizable, allowing you to experiment with different rulesets, visual styles, and interactions. Here are some ways you can modify the project:
1. **Rulesets**: Adjust the `conditions` object in `sketch.js` to create new cellular automaton rules.
2. **Grid Size**: Modify the `GRID_SIZE` constant to change the resolution of the simulation.
3. **Brush Behavior**: Alter the `handleMouseInput()` function to change how user input affects the cells.
4. **Color Schemes**: Update the cell rendering in `updateCells()` to experiment with different color patterns.
5. **Neighborhoods**: Modify `calculateHood0()` and `calculateHood1()` to explore different neighborhood configurations.
## Inspiration and Further Exploration
This project draws inspiration from the work of Slackermanz on Multiple Neighborhood Cellular Automata. To dive deeper into the subject, consider exploring:
- Cellular automaton theory
- Complexity science
- Generative art techniques
- Computational aesthetics
By experimenting with DigitalOrganism, you can gain insights into how simple rules can lead to complex, emergent behaviors—a fundamental concept in both design and natural systems.
## Get Started
Open `index.html` in a modern web browser to run the simulation. Click and drag on the canvas to interact with the cells and observe how patterns evolve over time.
Happy exploring!