DocumentCode :
2978003
Title :
Genetic algorithms for analogical mapping
Author :
Tessem, Bjornar
Author_Institution :
Dept. of Inf. Sci., Bergen Univ., Norway
fYear :
1998
fDate :
4-9 May 1998
Firstpage :
672
Lastpage :
677
Abstract :
The paper presents an application of genetic algorithms in analogical reasoning. Analogical reasoning means to utilize structural and semantic similarities between relational descriptions of two situations to establish new knowledge in one of the two situations. The author exploits the properties of genetic algorithms as a method to solve discrete optimization problems with many local optima. The author focuses on the mapping phase of analogical reasoning, and represents this problem as an objective function to be optimized by genetic algorithms. Examples and experiments indicate that the approach has expressibility and efficiency comparable to previous analogical mapping algorithms
Keywords :
case-based reasoning; genetic algorithms; analogical mapping; analogical reasoning; discrete optimization problems; efficiency; expressibility; genetic algorithms; local optima; objective function; relational descriptions; semantic similarities; structural similarities; Artificial intelligence; Engines; Genetic algorithms; Information science; Learning; Optimization methods; Space exploration; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4869-9
Type :
conf
DOI :
10.1109/ICEC.1998.700120
Filename :
700120
Link To Document :
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