A qualitative physics based on confluences
Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Artificial Intelligence
Causality and model abstraction
Artificial Intelligence
Generative design rationale: beyond the record and replay paradigm
Design rationale
Learning Why by Being Told What: Interactive Acquisition of Justifications
IEEE Expert: Intelligent Systems and Their Applications
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
An agent-based approach for coordinating product design workflows
Computers in Industry
Worlds and transformations: Supporting the sharing and reuse of engineering design knowledge
International Journal of Human-Computer Studies
An agent-based approach for coordinating product design workflows
Computers in Industry
Building up and reasoning about architectural knowledge
QoSA'06 Proceedings of the Second international conference on Quality of Software Architectures
Advanced Engineering Informatics
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The value of comprehensive rationale for documenting a design has long been recognized. However, designers rarely produce detailed rationale in practice because of the substantial time investment required. Efforts to support the acquisition of rationale information have focused on languages and tools for structuring the acquisition process, but still require substantial involvement on the part of the designer. This paper describes an experimental system, the Rationale Construction Framework (RCF), that acquires rationale information for the detailed design process without disrupting a designer's normal activities. The underlying approach involves monitoring designer interactions with a commercial computer-assisted design (CAD) tool to produce a rich process history. This history is subsequently structured and interpreted relative to a background theory of design metaphors that enable explanation of certain aspects of the design process. The framework provides an environment that can acquire rich, meaningful rationale information in a time- and cost-effective manner, with minimal disruption to the designer.