| | --- |
| | title: Digital Life Evolution Simulator |
| | emoji: 🧬 |
| | colorFrom: blue |
| | colorTo: red |
| | sdk: static |
| | pinned: false |
| | short_description: A self-evolving ecosystem that runs entirely in the browser |
| | --- |
| | |
| | # Digital Life Evolution Simulator |
| |
|
| | A self-evolving AI ecosystem where autonomous entities compete, reproduce, and adapt through neural networks and genetic algorithms. Watch digital life emerge and evolve in real-time. |
| |
|
| | ## What It Does |
| |
|
| | This simulation creates a population of AI entities with unique genomes that control their behavior through neural networks. Each entity: |
| |
|
| | - **Perceives** its environment (food, energy, other entities) |
| | - **Decides** actions based on neural network processing |
| | - **Adapts** through natural selection - successful traits get passed to offspring |
| | - **Evolves** over generations as mutations introduce variation |
| |
|
| | Four entity types exist: |
| |
|
| | - **Gatherers** - Collect food and energy efficiently |
| | - **Predators** - Hunt and consume other entities |
| | - **Builders** - Create structures and territorial markers |
| | - **Explorers** - Scavenge and discover new resources |
| |
|
| | ## Quick Start |
| |
|
| | ```bash |
| | # Start a local server |
| | npx serve . |
| | # or |
| | python3 -m http.server 8000 |
| | |
| | # Open in browser |
| | http://localhost:8000 |
| | ``` |
| |
|
| | ## Features |
| |
|
| | - **Neural Network AI** - Each entity has a unique brain with 80+ configurable parameters |
| | - **Genetic Algorithm** - Reproduction with crossover and mutation |
| | - **Spatial Awareness** - Efficient spatial hashing for proximity detection |
| | - **Real-time Stats** - Track population, generations, fitness, and neural activity |
| | - **Visual Feedback** - See neural network activations while watching decisions |
| |
|
| | ## Tech Stack |
| |
|
| | - Pure vanilla JavaScript (ES2022 modules) |
| | - HTML5 Canvas rendering |
| | - No build step, no dependencies |
| |
|
| | ## Project Structure |
| |
|
| | ``` |
| | js/ |
| | ├── ecosystem.js # Main loop, initialization |
| | ├── world.js # Environment, resource spawning |
| | ├── entities.js # Entity behavior logic |
| | ├── entityManager.js # Lifecycle management |
| | ├── genetics.js # Genome creation, reproduction |
| | ├── neuralNetwork.js # AI decision-making |
| | ├── particles.js # Visual effects |
| | ├── stats.js # Performance telemetry |
| | ├── ui.js # Controls, event logs |
| | └── utils.js # Math, object pools, spatial grid |
| | ``` |
| |
|
| | ## How Evolution Works |
| |
|
| | 1. **Selection** - Entities with higher fitness are more likely to reproduce |
| | 2. **Crossover** - Two parents combine their neural network weights |
| | 3. **Mutation** - Random Gaussian noise introduces variation |
| | 4. **Survival** - Less fit entities die; successful traits propagate |
| |
|
| | Over time, you'll observe emergent behaviors as entities adapt to the competitive environment. |
| |
|
