An Adaptive GP Strategy for Evolving Digital Circuits

Authors:
Mihai Oltean;Laura Dioşan
Affiliations:
Department of Computer Science, Faculty of Mathematics and Computer Science, Babeş-Bolyai University, Cluj-Napoca, Romania;Department of Computer Science, Faculty of Mathematics and Computer Science, Babeş-Bolyai University, Cluj-Napoca, Romania and Laboratoire d'Informatique, de Traitement de l'Information et de ...
Venue:
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
Year:
2008

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Abstract

The aim of this research is to develop an adaptive system for designing digital circuits. The investigated system, called Adaptive Genetic Programming (AdGP) contains most of the features required by an adaptive GP algorithm: it can decide the chromosome depth, the population size and the nodes of the GP tree which are the best suitable to provide the desired outputs. We have tested AdGP algorithm by solving some well-known problems in the field of digital circuits. Numerical experiments show that AdGP is able to perform very well on the considered test problems being able to successfully compete with standard GP having manually set parameters.