The Structure-Mapping Engine: Algorithm and Examples.
ILLINOIS UNIV AT URBANA DEPT OF COMPUTER SCIENCE
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This paper describes the Structure-Mapping Engine SME, a program for studying analogical processing. SME is based on Gentners Structure-Mapping theory of analogy, and provides a tool kit for constructing matching algorithms consistent with this theory. Its flexibility enhances cognitive simulation studies by simplifying experimentation. Furthermore, SME is very efficient, making it a useful component in machine learning systems as well. We review the Structure-Mapping theory and describe the design of the engine. We analyze the complexity of the algorithm, and demonstrate that most of the steps are polynomial, typically bounded by theta N sq. We demonstrate some examples of its operation taken from our cognitive simulation studies and work in machine learning, and then we compare SME to other analogy programs