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

التفاصيل البيبلوغرافية
العنوان: Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction
المؤلفون: Arcas, Blaise Agüera y, Alakuijala, Jyrki, Evans, James, Laurie, Ben, Mordvintsev, Alexander, Niklasson, Eyvind, Randazzo, Ettore, Versari, Luca
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence, F.2.2, I.2.11
الوصف: 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.
Comment: 20 pages; updated introduction with further related work
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2406.19108
رقم الأكسشن: edsarx.2406.19108
قاعدة البيانات: arXiv