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This chapter provides a brief overview of the shape computation research at the University of Sydney that was carried out over a 35-year period, between 1977 and 2012, referencing 17 Ph.D theses that discuss shape computation during that period. The chapter draws distinctions between shape computation using shape grammars and other approaches that parallel, supplement and diverge from shape grammars. It introduces a variety of methods for shape computation, including those based on infinite maximal lines, artificial intelligence, learning representations, learning generation rules, logic models, qualitative representation, qualitative reasoning, algebraic representation, shape semantics, situated learning, and shape interpretation.

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Shape Computation Research at the University of Sydney

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    2025年

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  • John Gero

摘要

This chapter provides a brief overview of the shape computation research at the University of Sydney that was carried out over a 35-year period, between 1977 and 2012, referencing 17 Ph.D theses that discuss shape computation during that period. The chapter draws distinctions between shape computation using shape grammars and other approaches that parallel, supplement and diverge from shape grammars. It introduces a variety of methods for shape computation, including those based on infinite maximal lines, artificial intelligence, learning representations, learning generation rules, logic models, qualitative representation, qualitative reasoning, algebraic representation, shape semantics, situated learning, and shape interpretation.