Self-Replicating Machines in Continuous Space with Virtual Physics

TL;DR

JohnnyVon demonstrates self-replicating machines in a continuous 2D space using particles governed by virtual physics, capable of replicating arbitrary patterns and spontaneously forming self-replicating structures.

Contribution

Introduces a virtual physics-based model of self-replicating machines in continuous space with autonomous pattern replication and spontaneous self-assembly.

Findings

Particles can assemble into arbitrary bit-encoded patterns.

Seed patterns can self-replicate in a particle soup.

Spontaneous formation of self-replicating patterns occurs over time.

Abstract

JohnnyVon is an implementation of self-replicating machines in continuous two-dimensional space. Two types of particles drift about in a virtual liquid. The particles are automata with discrete internal states but continuous external relationships. Their internal states are governed by finite state machines but their external relationships are governed by a simulated physics that includes Brownian motion, viscosity, and spring-like attractive and repulsive forces. The particles can be assembled into patterns that can encode arbitrary strings of bits. We demonstrate that, if an arbitrary "seed" pattern is put in a "soup" of separate individual particles, the pattern will replicate by assembling the individual particles into copies of itself. We also show that, given sufficient time, a soup of separate individual particles will eventually spontaneously form self-replicating patterns. We discuss the implications of JohnnyVon for research in nanotechnology, theoretical biology, and artificial life.