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Generative Design workflows have introduced alternative paradigms in thedomain of computational design, allowing designers to generate large pools ofvalid solutions by defining a set of goals and constraints. However, analyzingand narrowing down the generated solution space, which usually consists ofvarious high-dimensional properties, has been a major challenge in currentgenerative workflows. By taking advantage of the interactive unbounded spatialexploration, and the visual immersion offered in virtual reality platforms, wepropose V-Dream, a virtual reality generative analysis framework for exploringlarge-scale solution spaces. V-Dream proposes a hybrid search workflow in whicha spatial stochastic search approach is combined with a recommender systemallowing users to pick desired candidates and eliminate the undesired onesiteratively. In each cycle, V-Dream reorganizes the remaining options inclusters based on the defined features. Moreover, our framework allows users toinspect design solutions and evaluate their performance metrics in varioushierarchical levels, assisting them in narrowing down the solution spacethrough iterative cycles of search/select/re-clustering of the solutions in animmersive fashion. Finally, we present a prototype of our proposed framework,illustrating how users can navigate and narrow down desired solutions from apool of over 16000 monitor stands generated by Autodesk's Dreamcatchersoftware.

V-Dream: Immersive Exploration of Generative Design Solution Space