The Influence of Probabilistic Grammars on Evolution
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{megane:2023:GECCOcomp,
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author = "Jessica Megane and Nuno Lourenco and
Penousal Machado and Dirk Schweim",
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title = "The Influence of Probabilistic Grammars on Evolution",
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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 = "611--614",
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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, grammatical
evolution, probabilistic: Poster",
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isbn13 = "9798400701191",
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DOI = "doi:10.1145/3583133.3590706",
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size = "4 pages",
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abstract = "Context-Free Grammars (CFGs) are used in Genetic
Programming (GP) to encode the structure and syntax of
programs, enabling efficient exploration of potential
solutions and generation of well-formed and
syntactically correct programs. Probabilistic
Context-Free Grammars (PCFG) can be used to model the
distribution of solutions to help guide the search
process. Structured Grammatical Evolution (SGE) is a
grammar-based GP algorithm that uses a list of dynamic
lists as its genotype, where each list represents the
ordered indexes of production rules to expand for each
non-terminal in the grammar. Two recent variants
incorporate PCFG into the SGE framework, where the
probabilities of the production rule change during the
evolutionary process, resulting in improved
performance.This study examines the impact of these
differences on the behavior of SGE and its variants,
Probabilistic Structured Grammatical Evolution (PSGE)
and Co-evolutionary Probabilistic Structured
Grammatical Evolution (Co-PSGE), in terms of population
tree depth, genotype size, new solutions generated, and
runtime. The results indicate that the use of
probabilistic alternatives can affect the growth of
tree depth and size and increases the ability to
generate new solutions.",
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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
Jessica Megane
Nuno Lourenco
Penousal Machado
Dirk Schweim
Citations