# Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction

arXiv: https://arxiv.org/abs/2406.19108 · HTML: https://mlsanity.com/paper/2406.19108/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 40 references that are in the map.
- First posted on arXiv 27 Jun 2024.

## Builds on (most cited first, 2 of 2)

- [Self-Replication, Spontaneous Mutations, and Exponential Genetic Drift in Neural Cellular Automata](https://mlsanity.com/paper/2305.13043/) (2023)
- [Emergence of Self-Reproducing Metabolisms as Recursive Algorithms in an Artificial Chemistry](https://mlsanity.com/paper/2103.08245/) (2021)

## Built on by (most cited first, 2 of 2)

- [Automating the Search for Artificial Life with Foundation Models](https://mlsanity.com/paper/2412.17799/) (2024)
- [Tapes Together Strong: The Co-evolution of Computation and Cooperation](https://mlsanity.com/paper/2609.10817/) (2026)

## Abstract (arXiv)

The fields of Origin of Life and Artificial Life both question what life is and how it emerges from a distinct set of "pre-life" dynamics. One common feature of most substrates where life emerges is a marked shift in dynamics when self-replication appears. While there are some hypotheses regarding how self-replicators arose in nature, we know very little about the general dynamics, computational principles, and necessary conditions for self-replicators to emerge. This is especially true on "computational substrates" where interactions involve logical, mathematical, or programming rules. In this paper we take a step towards understanding how self-replicators arise by studying several computational substrates based on various simple programming languages and machine instruction sets. We show that when random, non self-replicating programs are placed in an environment lacking any explicit fitness landscape, self-replicators tend to arise. We demonstrate how this occurs due to random interactions and self-modification, and can happen with and without background random mutations. We also show how increasingly complex dynamics continue to emerge following the rise of self-replicators. Finally, we show a counterexample of a minimalistic programming language where self-replicators are possible, but so far have not been observed to arise.