Flow of Control in Linear Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Schonfeld:2015:CEC,
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author = "Justin Schonfeld and Daniel Ashlock",
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title = "Flow of Control in Linear Genetic Programming",
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booktitle = "Proceedings of 2015 IEEE Congress on Evolutionary
Computation (CEC 2015)",
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year = "2015",
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editor = "Yadahiko Murata",
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pages = "1175--1182",
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address = "Sendai, Japan",
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month = "25-28 " # may,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-4799-7491-7",
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URL = "http://eldar.mathstat.uoguelph.ca/dashlock/eprints/AFC.pdf",
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DOI = "doi:10.1109/CEC.2015.7257022",
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abstract = "Traditional flow of control for linear genetic
programming includes structures such as if-then-else
statements combined with gotos. In this study we
examine additional classes of flow of control
structures. The first is called the alternator. This is
a deterministically variable flow of control that
executes a goto every other time it is accessed. We
demonstrate that evolution can use alternators that
jump past one another to create solutions with
significantly more complexity than those created by
solutions without alternators for a simple binary
string generation problem. The alternator, while
clearly useful, would be difficult for human
programmers to use effectively. The alternator thus
demonstrates a strong disjunction between
human-friendly and evolution-friendly programming
languages. Domain specific flow of control structures
tailored to the environment being studied are also
examined. These are statements carefully designed for
the problems being solved. Allowing controllers solving
the Tartarus task to change the flow of control based
on knowledge of their position in the interior boundary
of a world substantially enhances the performance of
the controllers. Comparison of the three different
fitness functions used demonstrates that the benefit of
the alternate flow-of-control is domain specific.",
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notes = "1355 hrs 15464 CEC2015",
- }
Genetic Programming entries for
Justin Schonfeld
Daniel Ashlock
Citations