# Lenia - Biology of Artificial Life

**Authors:** Bert Wang-Chak Chan

arXiv: 1812.05433 · 2021-07-12

## TL;DR

Lenia is a novel two-dimensional cellular automaton system supporting diverse, complex, and life-like patterns that resemble microscopic organisms, offering insights into artificial life, biology, and AI.

## Contribution

Introduces Lenia, a continuous-space cellular automaton supporting a vast diversity of life-like patterns, with a comprehensive taxonomy and analysis of their properties and behaviors.

## Key findings

- Over 400 species identified in 18 families
- Patterns exhibit resilience, adaptability, and complex behaviors
- Potential mechanisms for self-propulsion and organization proposed

## Abstract

We report a new system of artificial life called Lenia (from Latin lenis "smooth"), a two-dimensional cellular automaton with continuous space-time-state and generalized local rule. Computer simulations show that Lenia supports a great diversity of complex autonomous patterns or "lifeforms" bearing resemblance to real-world microscopic organisms. More than 400 species in 18 families have been identified, many discovered via interactive evolutionary computation. They differ from other cellular automata patterns in being geometric, metameric, fuzzy, resilient, adaptive, and rule-generic.   We present basic observations of the system regarding the properties of space-time and basic settings. We provide a broad survey of the lifeforms, categorize them into a hierarchical taxonomy, and map their distribution in the parameter hyperspace. We describe their morphological structures and behavioral dynamics, propose possible mechanisms of their self-propulsion, self-organization and plasticity. Finally, we discuss how the study of Lenia would be related to biology, artificial life, and artificial intelligence.

## Full text

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## Figures

22 figures with captions in the complete paper: https://tomesphere.com/paper/1812.05433/full.md

## References

85 references — full list in the complete paper: https://tomesphere.com/paper/1812.05433/full.md

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Source: https://tomesphere.com/paper/1812.05433