Demonstrating the power of object-oriented genetic programming via the inference of graph models for complex networks

Traditionally, GP used a single tree-based representation which does not lend itself well to state-based programs or multiple behaviours. To alleviate this drawback, object-oriented GP (OOGP) introduced a means of evolving programs with multiple behaviours which could be easily extended to state-bas...

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Bibliographic Details

Published in:	2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014) pp. 305 - 311
Main Authors:	Medland, Michael Richard, Harrison, Kyle Robert, Ombuki-Berman, Beatrice M.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.07.2014
Subjects:	biologically inspired algorithms complex networks Computational modeling evolutionary computation genetic programming Genetics object-orientation Programming
Online Access:	Get full text
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