Abstract
In genetic algorithms, deception (i.e. false peaks in the fitness landscape) has long been recognised as an important barrier to performance however in genetic programming it has not received the recognition it deserves. In this and the next chapter we study two benchmark problems using the techniques described in the previous chapters. These show that deception is one of the reasons why these problems appear to be hard.
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© 2002 Springer-Verlag Berlin Heidelberg
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Langdon, W.B., Poli, R. (2002). Example I: The Artificial Ant. In: Foundations of Genetic Programming. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-04726-2_9
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DOI: https://doi.org/10.1007/978-3-662-04726-2_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-07632-9
Online ISBN: 978-3-662-04726-2
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