Abstract
This paper describes a general approach to support case-based structure generation named Conceptual Analogy (Börner 1997). The approach can be used to support design tasks in domains that do not allow the acquisition of a complete and consistent set of constraints or rules but that do provide a larger set of past experiences. The experiences – also called cases – may resemble for example CAD data of room layouts or pipe systems. Thus, cases represent solutions to particular problems without an explicit, a priori separation of problem and solution variables.The paper starts with a description and formalization of the case-based structure generation task and a discussion of why standard case-based reasoning and other approaches are not applicable.Then, the new approach of Conceptual Analogy (CA) is introduced. CA applies conceptual clustering to organize cases represented by graphs into hierarchical classes of structurally similar cases. These case classes are then represented by concepts. Given a problem, i.e., a partial solution, the hierarchy of concepts is searched for applicable concepts, i.e., concepts that allow the generation of at least one solution to the given problem. Applicable concepts are used to generate a set of solutions that can be ordered according to their quality. Properties of the approach as well as complexity results are presented. An architectural design domain and task where the approach has been applied successfully, is used for illustration and for practical evaluation.Finally, the approach and its implementation are compared to two systems that aim at the support of similar design tasks. The paper concludes with an assessment of the future direction of this research.
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Börner, K. Efficient Case-Based Structure Generation for Design Support. Artificial Intelligence Review 16, 87–118 (2001). https://doi.org/10.1023/A:1011610128253
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DOI: https://doi.org/10.1023/A:1011610128253