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

arXiv 2406.19108 ↗First posted 27 Jun 2024cs.NE cs.AIcited by 2

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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.

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

2 of 40 references.

References · 2

  1. 2023Self-Replication, Spontaneous Mutations, and Exponential Genetic Drift in Neural Cellular Automatacited by 8
  2. 2021Emergence of Self-Reproducing Metabolisms as Recursive Algorithms in an Artificial Chemistrycited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 0; 2026: 1.

2 papers.