The Design Argument Revisited through Evolutionary Computation: Imperfection, Robustness, and Creative Emergence.
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| Title: | The Design Argument Revisited through Evolutionary Computation: Imperfection, Robustness, and Creative Emergence. |
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| Authors: | Lumbreras, Sara (AUTHOR), Oviedo, Lluís (AUTHOR), Jeavons, Peter (AUTHOR) |
| Source: | Zygon: Journal of Religion & Science. Mar2026, Vol. 61 Issue 1, p221-239. 19p. |
| Subjects: | Evolutionary computation, Genetic algorithms, Heterogeneity, Adaptability (Personality), Imperfection, Phylogeny |
| Abstract: | This article offers a fresh perspective on the argument from design by drawing on modern evolutionary computation, which we propose as a more fruitful analogy for divine design than traditional craftsmanship models. We focus on genetic algorithms, which mimic biological evolution through operators that emulate combination, selection, and mutation, and bring new insights from practical experience with such algorithms. Far from being easy to implement, genetic algorithms require carefully designed codifications, operators, and parameters. Very importantly, in genetic algorithms, suboptimality emerges not as a flaw but as an essential trait: exploring imperfect solutions allows uncovering better, creative designs. In addition, imperfection is also linked to robustness: evolutionary outcomes are near optimal and flexible rather than finely tuned and fragile. Because genetic algorithms evolve a population of designs, diversity is both a requisite and a result. Building on the analogy between divine design and evolutionary computation, we argue that a divine designer would appear to value growth, adaptability, robustness, diversity, and creativity above static perfection. [ABSTRACT FROM AUTHOR] |
| Copyright of Zygon: Journal of Religion & Science is the property of Open Library of Humanities and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | This article offers a fresh perspective on the argument from design by drawing on modern evolutionary computation, which we propose as a more fruitful analogy for divine design than traditional craftsmanship models. We focus on genetic algorithms, which mimic biological evolution through operators that emulate combination, selection, and mutation, and bring new insights from practical experience with such algorithms. Far from being easy to implement, genetic algorithms require carefully designed codifications, operators, and parameters. Very importantly, in genetic algorithms, suboptimality emerges not as a flaw but as an essential trait: exploring imperfect solutions allows uncovering better, creative designs. In addition, imperfection is also linked to robustness: evolutionary outcomes are near optimal and flexible rather than finely tuned and fragile. Because genetic algorithms evolve a population of designs, diversity is both a requisite and a result. Building on the analogy between divine design and evolutionary computation, we argue that a divine designer would appear to value growth, adaptability, robustness, diversity, and creativity above static perfection. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 05912385 |
| DOI: | 10.16995/zygon.24840 |
