Implementation and Evaluation of a Novel ``Branch'' Construct for Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InCollection{gibbs:2002:IENBCGP,
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author = "Kevin A. Gibbs",
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title = "Implementation and Evaluation of a Novel
{``}Branch{''} Construct for Genetic Programming",
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booktitle = "Genetic Algorithms and Genetic Programming at Stanford
2002",
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year = "2002",
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editor = "John R. Koza",
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pages = "93--101",
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address = "Stanford, California, 94305-3079 USA",
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month = jun,
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publisher = "Stanford Bookstore",
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keywords = "genetic algorithms, genetic programming",
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URL = "http://www.genetic-programming.org/sp2002/Gibbs.pdf",
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language = "en",
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oai = "oai:CiteSeerXPSU:10.1.1.141.205",
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URL = "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.141.205",
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abstract = "This paper describes a technique for implementing a
novel type of {"}branch {"} operator within a genetic
programming system. This branch construct is a new
operator type that allows arbitrary branching from one
location in an individual{'}s execution tree to
another. The branch can be understood as alternatively
allowing arbitrary code reuse or approximating access
to a potentially infinite number of automatically
defined functions. This paper describes the proposed
design of this branch operator. This proposed design is
then implemented in a real world system, and the
performance effects of the branch operator are
evaluated in two well known genetic programming
problems: the artificial ant problem and the lawnmower
problem. [1,2] The branch is found to provide some
performance benefits in both of these problems, and
areas for further investigation are outlined.
Introduction and Overview In the day-to-day programming
done by humans, most all control structures in code
originate from a high level. Whether programming in a
low-level language like C or a higher-level language
like LISP, we are accustomed to using high-level
control constructs like functions, loops, if
statements, and recursion to control the path of
execution and maximize code reuse. The thought of using
a branch, or goto or jump",
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notes = "part of \cite{koza:2002:gagp} Artificial ant. Lawn
Mower. {"}allowing arbitrary code reuse{"} or
{"}potentially infinite number of ADFs{"}. Goto.
{"}branch{"} function with {"}random{"} destination
p95. Limits on total number of instructions and number
of branch instructions, defaults given if limits
reached. lilgp. Branch destinations stored as relative
offsets into the array of instructions.
",
- }
Genetic Programming entries for
Kevin A Gibbs
Citations