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Introduces Neural Particle Automata, a method for learning self-organizing particle dynamics using smooth particle hydrodynamics perception, enabling particles to have local perception vectors for an update rule, analogous to Neural Cellular Automata but on continuous particle positions.
This article explores neural cellular automata as a computational model inspired by biological morphogenesis and regeneration, demonstrating how simple local rules can lead to complex global behaviors.
CAX is a high-performance open-source library for cellular automata research, built on JAX. It accelerates simulations up to 2000x and supports discrete and continuous automata in arbitrary dimensions.