How did life arise on Earth?
It’s a question most people have wondered about at some point. As of 2025, there’s no scientific consensus on the answer. However, in 2024, a paper was published that answers a part of this mystery.
Abstract: 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.
We argue that this set of computational substrates shows a new way of discovering and arriving at life. The behavior of such systems is markedly different from auto-catalytic networks and biologically-inspired systems. Our analysis starts at the pre-life period as opposed to the experiments performed in Tierra and AVIDA where they began with hand-crafted self-replicators. Unlike previous work on computational substrates focused on pre-life where they observed self-replicators arise due to random initialization or mutation we showed that self-modification is the main culprit for self-replicator to arise in most of the experiments we performed. Moreover, our initial explorations and the ones observed in similar systems such as Tierra, AVIDA and Coreworld suggest that this may be just the beginning of the complexity of behaviors that can emerge and flourish in such systems.
You can read more about this self-replication experiment here. The code used in this experiment is open-source, and I was able to replicate the results on my laptop in under 15 minutes.