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

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arxiv 2406.19108 v2 pith:VY22EEH2 submitted 2024-06-27 cs.NE cs.AI

classification cs.NEcs.AI
keywords self-replicatorslifecomputationaldynamicsariseemergeprogrammingrandom
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Microcosmos: Reimagining Artificial Life for the GPU Era

    cs.NE 2026-07 accept novelty 7.0 of 10

    Microcosmos combines Cosserat-style elastic filaments with a lattice-Boltzmann fluid solver in a fully differentiable JAX engine, validated on hand-designed gaits, gradient folding, neuroevolution, quality-diversity s...

  2. Life as Plasmas: Autonomy and Interactivism in-materio

    cs.NE 2026-07 conditional novelty 6.5 of 10

    Dusty plasmas occupy the admissible non-equilibrium phase for minimal physical autonomy yet carry no informational heredity, separating physical life-candidacy from biological sufficiency.

  3. Replication and Information Extraction in a Minimal Agent-Environment Model

    cond-mat.dis-nn 2025-09 conditional novelty 6.0 of 10

    A self-labeling linear classifier can bootstrap alignment with the latent structure of Gaussian data when regularization is strong enough, and label-exchange between agents can produce collective consensus.

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