Adaptability and Homeostasis in the Game of Life interacting with the evolved Cellular Automata

TL;DR

This study explores how a two-layer cellular automata system can develop homeostasis through evolved interactions, revealing antagonistic attractors that regulate cell states, akin to biological systems like Daisy World.

Contribution

It introduces a novel two-layer cellular automata model with evolved rules that demonstrate emergent homeostasis and antagonistic attractors controlling cell populations.

Findings

Identified two antagonistic attractors controlling cell states.

Evolved rules effectively regulate the number of active cells.

Homeostasis dynamics resemble those in biological models like Daisy World.

Abstract

In this paper we study the emergence of homeostasis in a two-layer system of the Game of Life, in which the Game of Life in the first layer couples with another system of cellular automata in the second layer. Homeostasis is defined here as a space-time dynamic that regulates the number of cells in state-1 in the Game of Life layer. A genetic algorithm is used to evolve the rules of the second layer to control the pattern of the Game of Life. We discovered that there are two antagonistic attractors that control the numbers of cells in state-1 in the first layer. The homeostasis sustained by these attractors are compared with the homeostatic dynamics observed in Daisy World.