Towards Understanding and Refining the General Program Synthesis Benchmark Suite with Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{Forstenlechner:2018:CEC,
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author = "Stefan Forstenlechner and David Fagan and
Miguel Nicolau and Michael O'Neill",
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title = "Towards Understanding and Refining the General Program
Synthesis Benchmark Suite with Genetic Programming",
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booktitle = "2018 IEEE Congress on Evolutionary Computation (CEC)",
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year = "2018",
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editor = "Marley Vellasco",
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address = "Rio de Janeiro, Brazil",
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month = "8-13 " # jul,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/CEC.2018.8477953",
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abstract = "Program synthesis is a complex problem domain tackled
by many communities via different methods. In the last
few years, a lot of progress has been made with Genetic
Programming (GP) on solving a variety of general
program synthesis problems for which a benchmark suite
has been introduced. While Genetic Programming is
capable of finding correct solutions for many problems
contained in a general program synthesis problems
benchmark suite, the actual success rate per problem is
low in most cases. In this paper, we analyse certain
aspects of the benchmark suite and the computational
effort required to solve its problems. A subset of
problems on which GP performs poorly is identified.
This subset is analysed to find measures to increase
success rates for similar problems. The paper concludes
with suggestions to refine performance on program
synthesis problems.",
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notes = "WCCI2018",
- }
Genetic Programming entries for
Stefan Forstenlechner
David Fagan
Miguel Nicolau
Michael O'Neill
Citations