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From design experiences to generic mechanisms: Model-based learning in analogical design

Published online by Cambridge University Press:  27 February 2009

Sambasiva R. Bhatta  and
Ashok K. Goel
Sambasiva R. Bhatta
Affiliation:
College of Computing, Georgia Institute of Technology, Atlanta, GA 30332-0280, U.S.A.
Ashok K. Goel
Affiliation:
College of Computing, Georgia Institute of Technology, Atlanta, GA 30332-0280, U.S.A.
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Abstract

Analogical reasoning plays an important role in design. In particular, cross-domain analogies appear to be important in innovative and creative design. However, making cross-domain analogies is hard and often requires abstractions common to the source and target domains. Recent work in case-based design suggests that generic mechanisms are one type of abstractions useful in adapting past designs. However, one important yet unexplored issue is where these generic mechanisms come from. We hypothesize that they are acquired incrementally from design experiences in familiar domains by abstraction over patterns of regularity. Three important issues in abstraction from experiences are what to abstract from an experience, how far to abstract, and what methods to use. In this short paper, we describe how structure-behavior-function models of designs in a familiar domain provide the content, and together with the problem-solving context in which learning occurs, also provide the constraints for learning generic mechanisms from design experiences. In particular, we describe the model-based learning method with a scenario of learning feedback mechanism.

Keywords

AnalogyCased-based ReasoningCausal/Teleological MechanismsDesignModel-based Learning

Information

Type
Research Abstracts
Information
AI EDAM , Volume 10 , Issue 2: Special Issue: Machine learning in design , April 1996 , pp. 131 - 136
Copyright
Copyright © Cambridge University Press 1996

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References

REFERENCES

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