English

Self-Replicating Machines in Continuous Space with Virtual Physics

Neural and Evolutionary Computing 2020-08-20 v1 Computational Engineering, Finance, and Science Populations and Evolution

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.

Keywords

Cite

@article{arxiv.cs/0304022,
  title  = {Self-Replicating Machines in Continuous Space with Virtual Physics},
  author = {Arnold Smith and Peter Turney and Robert Ewaschuk},
  journal= {arXiv preprint arXiv:cs/0304022},
  year   = {2020}
}

Comments

39 pages, Java code available at http://purl.org/net/johnnyvon/