AI EDAM


Special Issue: Machine Learning in DesignGuest EditorsAlex H.B. DuffyDavid C. BrownAshok K. Goel

SPIDA: Abstracting and generalizing layout design cases


D. MANFAAT a1a2c1, A.H.B. DUFFY a1 and B.S. LEE a2
a1 CAD Centre, Department of Design, Manufacture and Engineering Management, University of Strathclyde, 75 Montrose Street, Glasgow G11XJ, Scotland, UK
a2 Department of Ship and Marine Technology, University of Strathclyde, 100 Montrose Street, Glasgow G40LZ, Scotland, UK

Abstract

Abstraction and generalization of layout design cases generate new knowledge that is more widely applicable to use than specific design cases. The abstraction and generalization of design cases into hierarchical levels of abstractions provide the designer with the flexibility to apply any level of abstract and generalized knowledge for a new layout design problem. Existing case-based layout learning (CBLL) systems abstract and generalize cases into single levels of abstractions, but not into a hierarchy. In this paper, we propose a new approach, termed customized viewpoint—spatial (CV–S), which supports the generalization and abstraction of spatial layouts into hierarchies along with a supporting system, SPIDA (SPatial Intelligent Design Assistant).

(Received June 27 1997)
(Revised October 17 1997)
(Accepted November 10 1997)


Key Words: Abstraction; Generalization; Machine Learning; Pattern Matching; Spatial Layout Design.

Correspondence:
c1 Reprint requests to: D. Manfaat, CAD Centre, Dept. of Design, Manufacture and Engineering Management, University of Strathclyde, 75 Montrose Street, Glasgow G11XJ, Scotland, UK. Tel: (+44) 141-552-4400; Fax: (+44) 141-552-3148; E-mail: joe@cad.strath.ac.uk.


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