Generating networks of genetic processors

Created by W.Langdon from gp-bibliography.bib Revision:1.8081

@Article{Campos:GPEM,

• author = "Marcelino Campos and Jose M. Sempere",
• title = "Generating networks of genetic processors",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2022",
• volume = "23",
• number = "1",
• pages = "133--155",
• month = mar,
• keywords = "genetic algorithms, genetic programming, Natural computing, Networks of bio-inspired processors, Parallel genetic algorithms, Formal languages, Descriptive complexity",
• ISSN = "1389-2576",
• URL = "https://rdcu.be/czY20",
• DOI = "doi:10.1007/s10710-021-09423-7",
• size = "23 pages",
• abstract = "The Networks of Genetic Processors (NGPs) are non-conventional models of computation based on genetic operations over strings, namely mutation and crossover operations as it was established in genetic algorithms. Initially, they have been proposed as acceptor machines which are decision problem solvers. In that case, it has been shown that they are universal computing models equivalent to Turing machines. we propose NGPs as enumeration devices and we analyze their computational power. First, we define the model and we propose its definition as parallel genetic algorithms. Once the correspondence between the two formalisms has been established, we carry out a study of the generation capacity of the NGPs under the research framework of the theory of formal languages. We investigate the relationships between the number of processors of the model and its generative power. Our results show that the number of processors is important to increase the generative capability of the model up to an upper bound, and that NGPs are universal models of computation if they are formulated as generation devices. This allows us to affirm that parallel genetic algorithms working under certain restrictions can be considered equivalent to Turing machines and, therefore, they are universal models of computation.",
• notes = "Valencian Research Institute for Artificial Intelligence, Universitat Politecnica de Valencia, Spain",

}

Genetic Programming entries for Marcelino Campos Frances Jose M Sempere

Citations