Abstract
Since its inception, πGE has used evolution to guide the order of how to construct derivation trees. It was hypothesised that this would allow evolution to adjust the order of expansion during the run and thus help with search. This research aims to identify if a specific order is reachable, how reachable it may be, and goes on to investigate what happens to the expansion order during a πGE run. It is concluded that within πGE we do not evolve towards a specific order but a rather distribution of orders. The added complexity that an evolvable order gives πGE can make it difficult to understand how it can effectively search, by examining the connectivity of the phenotypic landscape it is hoped to understand this. It is concluded that the addition of an evolvable derivation tree expansion order makes the phenotypic landscape associated with πGE very densely connected, with solutions now linked via a single mutation event that were not previously connected.
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Fagan, D., Hemberg, E., O’Neill, M., McGarraghy, S. (2013). Understanding Expansion Order and Phenotypic Connectivity in πGE. In: Krawiec, K., Moraglio, A., Hu, T., Etaner-Uyar, A.Ş., Hu, B. (eds) Genetic Programming. EuroGP 2013. Lecture Notes in Computer Science, vol 7831. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37207-0_4
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DOI: https://doi.org/10.1007/978-3-642-37207-0_4
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