- author = "Jessica Megane and Nuno Lourenco and Penousal Machado",
- title = "Co-evolutionary Probabilistic Structured Grammatical Evolution",
- booktitle = "Proceedings of the 2022 Genetic and Evolutionary Computation Conference",
- year = "2022",
- editor = "Alma Rahat and Jonathan Fieldsend and Markus Wagner and Sara Tari and Nelishia Pillay and Irene Moser and Aldeida Aleti and Ales Zamuda and Ahmed Kheiri and Erik Hemberg and Christopher Cleghorn and Chao-li Sun and Georgios Yannakakis and Nicolas Bredeche and Gabriela Ochoa and Bilel Derbel and Gisele L. Pappa and Sebastian Risi and Laetitia Jourdan and Hiroyuki Sato and Petr Posik and Ofer Shir and Renato Tinos and John Woodward and Malcolm Heywood and Elizabeth Wanner and Leonardo Trujillo and Domagoj Jakobovic and Risto Miikkulainen and Bing Xue and Aneta Neumann and Richard Allmendinger and Inmaculada Medina-Bulo and Slim Bechikh and Andrew M. Sutton and Pietro Simone Oliveto",
- pages = "991--999",
- address = "Boston, USA",
- series = "GECCO '22",
- month = "9-13 " # jul,
- organisation = "SIGEVO",
- publisher = "Association for Computing Machinery",
- publisher_address = "New York, NY, USA",
- keywords = "genetic algorithms, genetic programming, grammatical evolution, probabilistic algorithms, coevolution, grammar-based, gaussian mutation",
- isbn13 = "978-1-4503-9237-2",
-
URL = "
https://arxiv.org/abs/2204.08985",
-
DOI = "
doi:10.1145/3512290.3528833",
-
video_url = "https://vimeo.com/723973418",
-
code_url = "https://github.com/jessicamegane/co-psge",
- size = "9 pages",
- abstract = "This work proposes an extension to Structured Grammatical Evolution (SGE) called Co-evolutionary Probabilistic Structured Grammatical Evolution (Co-PSGE). In Co-PSGE each individual in the population is composed by a grammar and a genotype, which is a list of dynamic lists, each corresponding to a non-terminal of the grammar containing real numbers that correspond to the probability of choosing a derivation rule. Each individual uses its own grammar to map the genotype into a program. During the evolutionary process, both the grammar and the genotype are subject to variation operators.The performance of the proposed approach is compared to 3 different methods, namely, Grammatical Evolution (GE), Probabilistic Grammatical Evolution (PGE), and SGE on four different benchmark problems. The results show the effectiveness of the approach since Co-PSGE is able to outperform all the methods with statistically significant differences in the majority of the problems.",
-
notes = "Pagie polynomial, Boston Housing, 5-bit Even Parity,
11-bit Boolean Multiplexer
https://www.jessicamegane.pt/talk/co-evolutionary-probabilistic-structured-grammatical-evolution-at-gecco-2022/
GECCO-2022 A Recombination of the 31st International Conference on Genetic Algorithms (ICGA) and the 27th Annual Genetic Programming Conference (GP)",
