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

2024/06/27 by Blaise Agüera y Arcas, Arcas, Blaise Agüera y, Jyrki Alakuijala +13 · 20 voices · 9 citations
Computer Science · Decision Sciences · Engineering · Psychology · #Computability, Logic, AI Algorithms #Computer science #Epistemology #Human–computer interaction #Modular Robots and Swarm Intelligence #Philosophy #Psychology #Scientific Computing and Data Management #Simple (philosophy)

paper · pdf · doi:10.48550/arxiv.2406.19108

published in arXiv (Cornell University) (Cornell University)

openalex publication_date 2024/06/27 · openalex created_date 2024/06/29 · openalex updated_date 2026/07/28

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.

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