Introducing Petri Dish Neural Cellular Automata (PD-NCA) 🦠
The search for open-ended complexification, a north star of Artificial Life (ALife) simulations, is a question that fascinates us deeply. In this work we explore the role of continual adaptation in ALife simulation, where the cellular automata in our system do not rely on a fixed set of parameters, but rather learn continuously during the simulation itself.
Our Petri Dish Neural Cellular Automata (PD-NCA) is a new ALife substrate that consists of a differentiable world where multiple NCA learn to self-replicate and grow via ongoing gradient descent. Every individual is constantly trying to grow, all the while learning to adapt and out-compete its neighbors.
PD-NCA allows for complex, emergent behaviors like cyclic dynamics, territorial defense, and spontaneous cooperation. The video below shows the sheer variety and complexity that unfolds during several different simulations (each colour is a different NCA).