Genetic programming for solving common and domain-independent generic recursive problems
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{phillips:2017:CEC,
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author = "Tessa Phillips and Mengjie Zhang and Bing Xue",
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booktitle = "2017 IEEE Congress on Evolutionary Computation (CEC)",
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title = "Genetic programming for solving common and
domain-independent generic recursive problems",
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year = "2017",
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editor = "Jose A. Lozano",
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pages = "1279--1286",
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address = "Donostia, San Sebastian, Spain",
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publisher = "IEEE",
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isbn13 = "978-1-5090-4601-0",
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abstract = "In human written computer programs, loops and
recursion are very important structures. Many
real-world applications require recursion and loops.
Loops and recursion can also be achieved by using
genetic programming (GP). There has been a lot of work
on GP for loops but not much on recursion. Our recent
initial work on GP for recursion has shown that GP can
be used to solve recursion problems, based on which
this work develops two new GP methods that can solve a
wider range of problems without decreasing the
performance. The two new methods are tested on symbolic
regression problems, binary classification problems,
and Artificial Ant problems. They are compared to
methods using loops, traditional GP, and the methods
developed in our previous work. The results show that
the new methods have improved the accuracy and
increased the range of symbolic regression problems
that the methods can perfectly solve, and improved the
performance on two of the Artificial Ant problems. The
new methods can also solve classification problems, and
have better performance than loops on many of these
tasks. This is the first work using recursion for
classification problems, and is the first design of a
generic recursive method for GP.",
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keywords = "genetic algorithms, genetic programming, pattern
classification, program control structures, regression
analysis, artificial ant problems, binary
classification problems, domain-independent generic
recursive problems, human written computer programs,
loops, recursion problems, symbolic regression
problems, Computer science, Computers, Design
methodology, Image recognition, Libraries, Navigation",
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isbn13 = "978-1-5090-4601-0",
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DOI = "doi:10.1109/CEC.2017.7969452",
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month = "5-8 " # jun,
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notes = "IEEE Catalog Number: CFP17ICE-ART Also known as
\cite{7969452}",
- }
Genetic Programming entries for
Tessa Phillips
Mengjie Zhang
Bing Xue
Citations