Model induction: a new source of CSP model redundancy

Authors:
Y. C. Law;J. H. M. Lee
Affiliations:
Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, China;Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong SAR, China
Venue:
Eighteenth national conference on Artificial intelligence
Year:
2002

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Abstract

Based on the notions of viewpoints, models, and channeling constraints, the paper introduces model induction, a systematic transformation of constraints in an existing model to constraints in another viewpoint. Meant to be a general CSP model operator, model induction is useful in generating redundant models, which can be further induced or combined with the original model or other mutually redundant models. We propose three ways of combining redundant models using model induction, model channeling, and model intersection. Experimental results on the Langford's problem confirm that our proposed combined models exhibit improvements in efficiency and robustness over the original single models.