2023
DOI: 10.3390/biomimetics8010048
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Broadening the Taxonomic Breadth of Organisms in the Bio-Inspired Design Process

Abstract: (1) Generating a range of biological analogies is a key part of the bio-inspired design process. In this research, we drew on the creativity literature to test methods for increasing the diversity of these ideas. We considered the role of the problem type, the role of individual expertise (versus learning from others), and the effect of two interventions designed to increase creativity—going outside and exploring different evolutionary and ecological “idea spaces” using online tools. (2) We tested these ideas … Show more

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Cited by 5 publications
(2 citation statements)
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“…It shows summarized statistics, such as medians and quartiles, and the data density along its range. It helps identify and analyze significant differences between two samples, offering insights into patterns and the data structure [69]. This way, we can appreciate that in instances fifteen and sixteen, the standard deviation is slight in the metaheuristics with DQL compared to native metaheuristics, especially PSODQL, BATDQL, and OPADQL.…”
Section: Resultsmentioning
confidence: 99%
“…It shows summarized statistics, such as medians and quartiles, and the data density along its range. It helps identify and analyze significant differences between two samples, offering insights into patterns and the data structure [69]. This way, we can appreciate that in instances fifteen and sixteen, the standard deviation is slight in the metaheuristics with DQL compared to native metaheuristics, especially PSODQL, BATDQL, and OPADQL.…”
Section: Resultsmentioning
confidence: 99%
“…It shows summarized statistics, such as medians and quartiles, and the data density along its range. It helps identify and analyze significant differences between two samples, offering insights into patterns and the data structure [ 78 ]. This way, we can appreciate that in instances fifteen and sixteen, the standard deviation is small in the metaheuristics with DQL compared to native metaheuristics, especially PSODQL, BATDQL, and OPADQL.…”
Section: Resultsmentioning
confidence: 99%