Mutual information-based fitness functions for evolutionary circuit synthesis

Author

Aguirre, Arturo Hernández ; Coello, Carlos A Coello

Author_Institution

Dept. of Comput. Sci., Center for Res. in Math., Guanajuato, Mexico

Volume

2

fYear

2004

fDate

19-23 June 2004

Firstpage

1309

Abstract

Entropy-based measures, such as mutual information and normalized mutual information are investigated as tools for similarity measures between the target and evolving circuit. Three fitness functions are built over a primitive one. We show that the search landscape of normalized mutual information looks more amenable for evolutionary computation algorithms than simple mutual information. The evolutionary synthesized circuits are compared to the known optimum size. A discussion of the potential of the information-theoretical approach is given.

Keywords

entropy; evolutionary computation; logic design; network synthesis; search problems; entropy-based measures; evolutionary circuit synthesis; evolutionary computation algorithms; evolutionary synthesized circuits; evolving circuit; information-theoretical approach; mutual information-based fitness functions; normalized mutual information; search landscape; similarity measures; target circuit; Boolean functions; Circuit synthesis; Circuit testing; Computer science; Entropy; Genetic communication; Genetic programming; Information theory; Logic circuits; Mutual information;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2004. CEC2004. Congress on

Print_ISBN

0-7803-8515-2

Type

conf

DOI

10.1109/CEC.2004.1331048

Filename

1331048