memlnaut-nisps/README.md

# Neural Interactive Shaping of Parameter Spaces

https://musicallyembodiedml.github.io/memlnaut/approaches/nisps

## Web Playground

Try NISPS in your browser — no hardware required:

```bash
cd playground
python3 -m http.server
# Open http://localhost:8000
```

Train a neural network to map joystick positions to generative visuals through interactive machine learning. Two learning modes: direct example mapping and reinforcement learning with thumbs up/down feedback.
Update project title and add reference link 2025-11-13 18:24:18 +01:00			`# Neural Interactive Shaping of Parameter Spaces`

			`https://musicallyembodiedml.github.io/memlnaut/approaches/nisps`

feat: add web-based interactive playground for NISPS Faithful JS port of nisps-core MLP + IML engine with a touch-friendly UI for exploring neural parameter mapping visually. Two learning modes: example-based (set slider targets) and RL feedback (thumbs up/down with exploration noise). Flow field particle system controlled by 8 MLP outputs. 2026-02-11 13:17:17 +01:00			`## Web Playground`
Update project title and add reference link 2025-11-13 18:24:18 +01:00
feat: add web-based interactive playground for NISPS Faithful JS port of nisps-core MLP + IML engine with a touch-friendly UI for exploring neural parameter mapping visually. Two learning modes: example-based (set slider targets) and RL feedback (thumbs up/down with exploration noise). Flow field particle system controlled by 8 MLP outputs. 2026-02-11 13:17:17 +01:00			`Try NISPS in your browser — no hardware required:`

			```bash
			`cd playground`
			`python3 -m http.server`
			`# Open http://localhost:8000`
			```

			`Train a neural network to map joystick positions to generative visuals through interactive machine learning. Two learning modes: direct example mapping and reinforcement learning with thumbs up/down feedback.`