HOTGP - Higher-Order Typed Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8178
- @InProceedings{fernandes:2023:GECCO,
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author = "Matheus Campos Fernandes and
Fabricio {Olivetti De Franca} and Emilio Francesquini",
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title = "{HOTGP} - {Higher-Order} Typed Genetic Programming",
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booktitle = "Proceedings of the 2023 Genetic and Evolutionary
Computation Conference",
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year = "2023",
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editor = "Sara Silva and Luis Paquete and Leonardo Vanneschi and
Nuno Lourenco and Ales Zamuda and Ahmed Kheiri and
Arnaud Liefooghe and Bing Xue and Ying Bi and
Nelishia Pillay and Irene Moser and Arthur Guijt and
Jessica Catarino and Pablo Garcia-Sanchez and
Leonardo Trujillo and Carla Silva and Nadarajen Veerapen",
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pages = "1091--1099",
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address = "Lisbon, Portugal",
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series = "GECCO '23",
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month = "15-19 " # jul,
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organisation = "SIGEVO",
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publisher = "Association for Computing Machinery",
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publisher_address = "New York, NY, USA",
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keywords = "genetic algorithms, genetic programming, functional
programming, inductive program synthesis",
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isbn13 = "9798400701191",
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DOI = "doi:10.1145/3583131.3590464",
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size = "9 pages",
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abstract = "Program synthesis is the process of generating a
computer program following a set of specifications,
which can be a high-level description of the problem
and/or a set of input-output examples. The synthesis
can be modeled as a search problem in which the search
space is the set of all the programs valid under a
grammar. As the search space is vast, brute force is
usually not viable and search heuristics, such as
genetic programming, also have difficulty navigating it
without any guidance. In this paper we present HOTGP, a
new genetic programming algorithm that synthesizes
pure, typed, and functional programs. HOTGP leverages
the knowledge provided by the rich data-types
associated with the specification and the built-in
grammar to constrain the search space and improve the
performance of the synthesis. The grammar is based on
Haskell's standard base library (the synthesized code
can be directly compiled using any standard Haskell
compiler) and includes support for higher-order
functions, Λ-functions, and parametric polymorphism.
Experimental results show that, when compared to 6
state-of-the-art algorithms using a standard set of
benchmarks, HOTGP is competitive and capable of
synthesizing the correct programs more frequently than
any other of the evaluated algorithms.",
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notes = "GECCO-2023 A Recombination of the 32nd International
Conference on Genetic Algorithms (ICGA) and the 28th
Annual Genetic Programming Conference (GP)",
- }
Genetic Programming entries for
Matheus Campos Fernandes
Fabricio Olivetti de Franca
Emilio Francesquini
Citations