A detailed analysis of a PushGP run
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{McPhee:2016:GPTP,
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author = "Nicholas Freitag McPhee and Mitchell D. Finzel and
Maggie M. Casale and Thomas Helmuth and Lee Spector",
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title = "A detailed analysis of a {PushGP} run",
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booktitle = "Genetic Programming Theory and Practice XIV",
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year = "2016",
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editor = "Rick Riolo and Bill Worzel and Brian Goldman and
Bill Tozier",
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pages = "65--83",
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address = "Ann Arbor, USA",
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month = "19-21 " # may,
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, PushGP,
ancestry graph, lineage, inheritance",
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isbn13 = "978-3-319-97087-5",
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URL = "https://www.springer.com/us/book/9783319970875",
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DOI = "doi:10.1007/978-3-319-97088-2_5",
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abstract = "In evolutionary computation runs there is a great deal
of data that could be saved and analysed. This data is
often put aside, however, in favour of focusing on the
final outcomes, typically captured and presented in the
form of summary statistics and performance plots. Here
we examine a genetic programming run in detail and
trace back from the solution to determine how it was
derived. To visualize this genetic programming run, the
ancestry graph is extracted, running from the
solution(s) in the final generation up to their
ancestors in the initial random population.
The key instructions in the solution are also
identified, and a genetic ancestry graph is
constructed, a subgraph of the ancestry graph
containing only those individuals contributed genetic
information (or instructions) to the solution. This
visualization and our ability to trace these key
instructions throughout the run allowed us to identify
general inheritance patterns and key evolutionary
moments in this run.",
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notes = "
Part of \cite{Tozier:2016:GPTP} published after the
workshop",
- }
Genetic Programming entries for
Nicholas Freitag McPhee
Mitchell Finzel
Maggie M Casale
Thomas Helmuth
Lee Spector
Citations