Neural Particle Automata
Neural CAs model self-organizing pattern formation on grids. Now the grid is gone. Each cell is an agentic particle that can move freely in space and change its state. While each particle follows a simple shared rule, many together can grow complex morphologies or form intricate patterns. The resulting particle system as a whole can regenerate from damage and exhibits surprising emergent behavior. Try cutting the lizard and watch it heal itself!
Neural Particle Automata launched on June 23, 2026 with 88 votes, #472 of 22,647 launches that month and more than 95% of that year's launches.
In plain words
Neural Particle Automata removes the grid from cellular automata by making each cell an independent particle that moves freely in space while following a shared rule. Multiple particles operating under simple instructions create complex, self-organizing patterns and morphologies that can regenerate after damage. The system demonstrates emergent behavior from collective particle interactions, allowing users to observe phenomena like a virtual organism healing itself after being cut.
written from the facts on this page · September 2026
From the sources
Neural Particle Automata: Learning Self-Organizing Particle Dynamics
This demo is not yet supported on iPhone devices . Please use desktop/laptop or Android devices. When changing $(\Delta x, \Delta y)$, we automatically adjust the value of $\Delta t$ to avoid the Euler integration from overshooting. In the Isotropic mode, the scaling factors are forced to be equal $\Delta x = \Delta y$. We introduce Neural Particle Automata (NPA), a Lagrangian generalization of Neural Cellular Automata (NCA) from static lattices to dynamic particle systems. Unlike classical Eulerian NCA where cells are fixed to pixels or voxels, NPA represent each cell as a particle with a continuous position and an internal state, both updated by a shared learnable neural rule. This…from selforg-npa.github.io
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High-Res Neural Cellular AutomataJun 2026 · cells2pixels.github.io · ▲208Neural CAs model self-organizing pattern formation. Now they can generate patterns at HD resolution in real-time, enabled by turning each CA cell into a Neural Field. Try 3 demos: grow a pattern from a seed (and damage it, it heals), synthesize PBR textures that can regenerate, or create 3D textures like clouds.
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