Abstract
The use of visual analogy is considered to be a most suitable aid for design problem solving. Reasoning by analogy deals with two main cognitive paradigms. The first one is concerned with schema-driven analogy, which is defined as the use of abstract experiential knowledge that can direct a design solution to a familiar problem type. The second paradigm has to do with precedent-driven analogy, and is distinguished by the use of a concrete prior design problem whose major components and its corresponding relationships could be explicitly mapped onto the problem at hand. In order to support the use of visual displays in design through schema-driven and precedent-driven cognitive strategies, an interactive computerized framework that applies knowledge management practices as well as artificial intelligence technology for supporting visual reasoning is proposed.
Citation
Dai, W., and Casakin, H. (2004) A Human-Computer Framework for Schema-Driven and Precedent-Driven Visual Analogy in Design., in Redmond, J., Durling, D. and de Bono, A (eds.), Futureground - DRS International Conference 2004, 17-21 November, Melbourne, Australia. https://dl.designresearchsociety.org/drs-conference-papers/drs2004/researchpapers/103
A Human-Computer Framework for Schema-Driven and Precedent-Driven Visual Analogy in Design.
The use of visual analogy is considered to be a most suitable aid for design problem solving. Reasoning by analogy deals with two main cognitive paradigms. The first one is concerned with schema-driven analogy, which is defined as the use of abstract experiential knowledge that can direct a design solution to a familiar problem type. The second paradigm has to do with precedent-driven analogy, and is distinguished by the use of a concrete prior design problem whose major components and its corresponding relationships could be explicitly mapped onto the problem at hand. In order to support the use of visual displays in design through schema-driven and precedent-driven cognitive strategies, an interactive computerized framework that applies knowledge management practices as well as artificial intelligence technology for supporting visual reasoning is proposed.