BFF: Simple explanations for complex phenomena
For researchers studying artificial life and self-replication, this work refines understanding of necessary conditions for emergence, though the findings are incremental.
The paper challenges the claim that paired interactions are necessary for finding self-replicators in a computational soup, showing that simple mutation random walks are equally effective, and that capping ancestry tree depth/width only prevents takeover, not emergence.
The ''Computational Life'' paper (Agüera y Arcas et al., 2024) argues that paired interactions in a computational soup are an effective way to find self-replicators. In this work, aided by recent developments in self-replicator detection, we explore the alternate hypothesis that self-replicators can be found at least as easily using simple mutation random walks in program space. We also explore the claim that capping the maximum ''depth'' and ''width'' of the ancestry tree stops self-replicators from emerging, showing instead that it merely stops self-replicators from taking over the soup.