Self-Reproduction and Evolution in Cellular Automata: 25 Years after Evoloops
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866910736633036800 |
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| author | Sayama, Hiroki Nehaniv, Chrystopher L. |
| author_facet | Sayama, Hiroki Nehaniv, Chrystopher L. |
| contents | The year of 2024 marks the 25th anniversary of the publication of evoloops, an evolutionary variant of Chris Langton's self-reproducing loops which proved constructively that Darwinian evolution of self-reproducing organisms by variation and natural selection is possible within deterministic cellular automata. Over the last few decades, this line of Artificial Life research has since undergone several important developments. Although it experienced a relative dormancy of activities for a while, the recent rise of interest in open-ended evolution and the success of continuous cellular automata models have brought researchers' attention back to how to make spatio-temporal patterns self-reproduce and evolve within spatially distributed computational media. This article provides a review of the relevant literature on this topic over the past 25 years and highlights the major accomplishments made so far, the challenges being faced, and promising future research directions. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2402_03961 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Self-Reproduction and Evolution in Cellular Automata: 25 Years after Evoloops Sayama, Hiroki Nehaniv, Chrystopher L. Cellular Automata and Lattice Gases Neural and Evolutionary Computing Pattern Formation and Solitons Populations and Evolution The year of 2024 marks the 25th anniversary of the publication of evoloops, an evolutionary variant of Chris Langton's self-reproducing loops which proved constructively that Darwinian evolution of self-reproducing organisms by variation and natural selection is possible within deterministic cellular automata. Over the last few decades, this line of Artificial Life research has since undergone several important developments. Although it experienced a relative dormancy of activities for a while, the recent rise of interest in open-ended evolution and the success of continuous cellular automata models have brought researchers' attention back to how to make spatio-temporal patterns self-reproduce and evolve within spatially distributed computational media. This article provides a review of the relevant literature on this topic over the past 25 years and highlights the major accomplishments made so far, the challenges being faced, and promising future research directions. |
| title | Self-Reproduction and Evolution in Cellular Automata: 25 Years after Evoloops |
| topic | Cellular Automata and Lattice Gases Neural and Evolutionary Computing Pattern Formation and Solitons Populations and Evolution |
| url | https://arxiv.org/abs/2402.03961 |