Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction
Fuente:
arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866909277211328512 |
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| author | Arcas, Blaise Agüera y Alakuijala, Jyrki Evans, James Laurie, Ben Mordvintsev, Alexander Niklasson, Eyvind Randazzo, Ettore Versari, Luca |
| author_facet | Arcas, Blaise Agüera y Alakuijala, Jyrki Evans, James Laurie, Ben Mordvintsev, Alexander Niklasson, Eyvind Randazzo, Ettore Versari, Luca |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_19108 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction Arcas, Blaise Agüera y Alakuijala, Jyrki Evans, James Laurie, Ben Mordvintsev, Alexander Niklasson, Eyvind Randazzo, Ettore Versari, Luca Neural and Evolutionary Computing Artificial Intelligence F.2.2; I.2.11 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. |
| title | Computational Life: How Well-formed, Self-replicating Programs Emerge from Simple Interaction |
| topic | Neural and Evolutionary Computing Artificial Intelligence F.2.2; I.2.11 |
| url | https://arxiv.org/abs/2406.19108 |