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While structural optimisation is usually handled by iterative methods requiring repeated samples of a physics-based model, this process can be computationally demanding. Given a set of previously optimised structures of the same topology, this paper uses inductive learning to replace this optimisation process entirely by deriving a function that directly(More)
Style is a broad term that could potentially refer to any features of a work, as well as a fluid concept that is subject to change and disagreement. A similarly flexible method of representing style is proposed based on the idea of an archetype, to which real designs can be compared, and tested with examples of architectural plans. Unlike a fixed, symbolic(More)
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examples of previous designs, thus implicitly capturing the features that distinguish that set from others without requiring a predetermined measure of fitness. A genetic algorithm is(More)