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Evolutionary learning of novel grammars for design improvement

Published online by Cambridge University Press:  27 February 2009

John S. Gero ,
Sushil J. Louis  and
Sourav Kundu
John S. Gero
Affiliation:
Key Centre of Design Computing, Department of Architectural and Design Science, University of Sydney, Sydney NSW 2006, Australia
Sushil J. Louis
Affiliation:
Key Centre of Design Computing, Department of Architectural and Design Science, University of Sydney, Sydney NSW 2006, Australia
Sourav Kundu
Affiliation:
Key Centre of Design Computing, Department of Architectural and Design Science, University of Sydney, Sydney NSW 2006, Australia
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Abstract

This paper focuses on that form of learning that relates to exploration, rather than generalization. It uses the notion of exploration as the modification of state spaces within which search and decision making occur. It demonstrates that the genetic algorithm formalism provides a computational construct to carry out this learning. The process is exemplified using a shape grammar for a beam section. A new shape grammar is learned that produces a new state space for the problem. This new state space has improved characteristics.

Keywords

EvolutionGenetic AlgorithmsLearningShape Grammars
Type
Articles
Information
AI EDAM , Volume 8 , Issue 2 , Spring 1994 , pp. 83 - 94
Copyright
Copyright © Cambridge University Press 1994

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