A predator-prey model based on fully parallel cellular automata

TL;DR

This paper introduces a fully parallel cellular automata predator-prey model with moveable wolves and sheep, incorporating genetic traits, reproduction, and neighborhood dynamics to study population evolution.

Contribution

It presents a novel fully parallel cellular automata framework with a new neighborhood definition for predator-prey interactions, including genetic and reproductive behaviors.

Findings

Initial population densities influence evolution dynamics

Mutation rate affects genetic diversity and stability

Lattice size impacts population oscillations

Abstract

We presented a predator-prey lattice model containing moveable wolves and sheep, which are characterized by Penna double bit strings. Sexual reproduction and child-care strategies are considered. To implement this model in an efficient way, we build a fully parallel Cellular Automata based on a new definition of the neighborhood. We show the roles played by the initial densities of the populations, the mutation rate and the linear size of the lattice in the evolution of this model.