Flow-Lenia: Emergent evolutionary dynamics in mass conservative continuous cellular automata

TL;DR

Flow-Lenia introduces a mass conservative extension to Lenia, enabling the emergence of complex, self-organizing patterns and multispecies dynamics through evolutionary processes in continuous cellular automata.

Contribution

It presents a novel mass conservative continuous CA model, Flow-Lenia, with embedded parameters allowing for emergent evolution and complex creature behaviors.

Findings

Flow-Lenia effectively generates spatially-localized patterns with complex behaviors.

Parameters can be optimized to produce interesting creature behaviors.

The system supports multispecies simulations with embedded parameter dynamics.

Abstract

Central to the artificial life endeavour is the creation of artificial systems spontaneously generating properties found in the living world such as autopoiesis, self-replication, evolution and open-endedness. While numerous models and paradigms have been proposed, cellular automata (CA) have taken a very important place in the field notably as they enable the study of phenomenons like self-reproduction and autopoiesis. Continuous CA like Lenia have been showed to produce life-like patterns reminiscent, on an aesthetic and ontological point of view, of biological organisms we call creatures. We propose in this paper Flow-Lenia, a mass conservative extension of Lenia. We present experiments demonstrating its effectiveness in generating spatially-localized patters (SLPs) with complex behaviors and show that the update rule parameters can be optimized to generate complex creatures showing behaviors of interest. Furthermore, we show that Flow-Lenia allows us to embed the parameters of the model, defining the properties of the emerging patterns, within its own dynamics thus allowing for multispecies simulations. By using the evolutionary activity framework as well as other metrics, we shed light on the emergent evolutionary dynamics taking place in this system.