A detailed analysis of a PushGP run

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

@InProceedings{McPhee:2016:GPTP,
  author =       "Nicholas Freitag McPhee and Mitchell D. Finzel and 
                 Maggie M. Casale and Thomas Helmuth and Lee Spector",
  title =        "A detailed analysis of a {PushGP} run",
  booktitle =    "Genetic Programming Theory and Practice XIV",
  year =         "2016",
  editor =       "Rick Riolo and Bill Worzel and Brian Goldman and 
                 Bill Tozier",
  address =      "Ann Arbor, USA",
  month =        "19-21 " # may,
  publisher =    "Springer",
  note =         "Forthcoming",
  keywords =     "genetic algorithms, genetic programming, PushGP,
                 ancestry graph, lineage, inheritance",
  isbn13 =       "978-3-319-97087-5",
  URL =          "https://www.springer.com/us/book/9783319970875",
  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.",
  notes =        "

                 Part of \cite{Tozier:2016:GPTP} to be published after
                 the workshop",
}

Genetic Programming entries for Nicholas Freitag McPhee Mitchell Finzel Maggie M Casale Thomas Helmuth Lee Spector

Citations