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.

研究原生与人工生命起源及自复制体在计算底层中的产生和动态，证明在缺少明确适应度地形的环境中，自复制体经由随机相互作用和自我修改可在计算底层中产生，并展示随着自复制体的崛起，逐渐出现更加复杂的动态。