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Empirical support for problem-solution coevolution in a parametric design environment
Journal article   Peer reviewed

Empirical support for problem-solution coevolution in a parametric design environment

Rongrong Yu, Ning Gu, Michael Ostwald and John S. Gero
AI EDAM, v 29(1), pp 33-44
01 Feb 2015

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Interdisciplinary Applications Engineering Engineering, Manufacturing Engineering, Multidisciplinary Science & Technology Technology
This paper describes the results of a protocol study exploring problem-solution coevolution in a parametric design environment (PDE). The study involved eight participants who completed a defined architectural design task using Rhino and Grasshopper software: a typical PDE. The method of protocol analysis was employed to study the cognitive behaviors that occurred while these designers were working in the PDE. By analyzing the way in which the designers shifted between "problem" and "solution" spaces in the PDE, characteristics of the coevolutionary design process are identified and discussed. Results of this research include two potentially significant observations. First, the coevolution process occurs frequently within the design knowledge level (i.e., when using Rhino) and within the rule algorithm level (i.e., when using Grasshopper) of the parametric design process. Second, the designers' coevolution process was focused on the design knowledge level at the beginning of the design session, while they focused more on the rule algorithm level toward the end of the design session. These results support an improved understanding of the design process that occurs in PDEs.

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