Combining top-down and bottom-up approaches for automated discovery of typed programs
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gp-bibliography.bib Revision:1.8010
- @InProceedings{Kren:2017:ieeeSSCIa,
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author = "Tomas Kren and Josef Moudrik and Roman Neruda",
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booktitle = "2017 IEEE Symposium Series on Computational
Intelligence (SSCI)",
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title = "Combining top-down and bottom-up approaches for
automated discovery of typed programs",
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year = "2017",
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abstract = "Automated program discovery has been mainly approached
via Genetic Programming, which represents the search
space of programs implicitly by a collection of
individuals. In this paper, we propose a way of
representing program search space explicitly, with a
top-down hierarchy of semi-constructed programs.
Together with a bottom-up generation procedure, we
maintain an overview of the overall search space
structure, while being able to quickly get samples from
the fringe. Moreover, having a type system with
parametric polymorphism allows us to limit the state
space size using type level programming while keeping a
complete control over program sizes. Our approach can
naturally be used for searching the space of programs
using tree search methods. We back this claim by a
simple experiment using a Monte-Carlo Tree Search
algorithm, though other search methods (such as A*)
might be used as well.",
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keywords = "genetic algorithms, genetic programming",
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DOI = "doi:10.1109/SSCI.2017.8285209",
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month = nov,
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notes = "Also known as \cite{8285209}",
- }
Genetic Programming entries for
Tomas Kren
Josef Moudrik
Roman Neruda
Citations