年代:1985 |
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Volume 1 issue 1
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11. |
Hierarchical arc consistency: exploiting structured domains in constraint satisfaction problems |
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Computational Intelligence,
Volume 1,
Issue 1,
1985,
Page 118-126
Alan K. Mackworth,
Jan A. Mulder,
William S. Havens,
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摘要:
Constraint satisfaction problems can be solved by network consistency algorithms that eliminate local inconsistencies before constructing global solutions. We describe a new algorithm that is useful when the variable domains can be structured hierarchically into recursive subsets with common properties and common relationships to subsets of the domain values for related variables. The algorithm, HAC, uses a technique known as hierarchical arc consistency. Its performance is analyzed theoretically and the conditions under which it is an improvement are outlined. The use of HAC in a program for understanding sketch maps, Mapsee3, is briefly discussed and experimental results consistent with the theory are reported.
ISSN:0824-7935
DOI:10.1111/j.1467-8640.1985.tb00064.x
出版商:Blackwell Publishing Ltd
年代:1985
数据来源: WILEY
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12. |
A theory of schema labelling |
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Computational Intelligence,
Volume 1,
Issue 1,
1985,
Page 127-139
William Havens,
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PDF (1357KB)
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摘要:
Schema labelling is a knowledge organization theory for recognition systems. In this theory, recognition constructs symbolic network descriptions of sensory data in terms of a stored knowledge base of schemas. A schema knowledge representation is formally specified. Each schema represents a class of objects by specifying class membership as a set of constraints on other classes. The constraints are based on two orthogonal relationships in knowledge organization: composition and specialization. Complex objects have internal structure which can be represented as composition constraints among their parts. Likewise, specialization constraints segment classes into subclasses by type. The description produced by schema labelling is a network consistency graph. The nodes of the graph are schema instances derived from the knowledge base. The domain for each instance is its finite set of subclasses and the network constraints are the constraints defined between schemas. Constraints are propagated in the network using an arc consistency algorithm mat has been adapted to schema representations. The constructed network description makes explicit the objects recognized in the data and their relationships. The graph is hierarchical, providing a description at multiple levels of detail. A hypothetical scene analysis system is used to illustrate the methodology.
ISSN:0824-7935
DOI:10.1111/j.1467-8640.1985.tb00065.x
出版商:Blackwell Publishing Ltd
年代:1985
数据来源: WILEY
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13. |
EDITORIAL/ÉDITORIAL |
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Computational Intelligence,
Volume 1,
Issue 1,
1985,
Page -
Nick Cercone,
Gordon McCalla,
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PDF (528KB)
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ISSN:0824-7935
DOI:10.1111/j.1467-8640.1985.tb00053.x
出版商:Blackwell Publishing Ltd
年代:1985
数据来源: WILEY
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