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Evolutionary Synthesis of Logic Circuits Using Information Theory
BibTeX
@MISC{Aguirre_evolutionarysynthesis,
author = {Arturo Hernández Aguirre and Carlos A. Coello},
title = {Evolutionary Synthesis of Logic Circuits Using Information Theory},
year = {}
}
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Abstract
Abstract. In this paper, we propose the use of Information Theory as the basis for designing a fitness function for Boolean circuit design using Genetic Programming. Boolean functions are implemented by replicating binary multiplexers. 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 landscape of Normalized Mutual Information is more amenable for being used as a fitness function 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.
Keyphrases
logic circuit using information theory fitness function evolutionary synthesis normalized mutual information entropy-based measure genetic programming binary multiplexer simple mutual information optimum size information theory similarity measure information-theoretical approach boolean function primitive one mutual information boolean circuit design
