Genetic programming with context-sensitive grammars

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@PhdThesis{paterson:thesis,

• author = "Norman Paterson",
• title = "Genetic programming with context-sensitive grammars",
• school = "Saint Andrew's University",
• year = "2002",
• address = "UK",
• month = sep,
• email = "norman@dcs.st-and.ac.uk",
• keywords = "genetic algorithms, genetic programming, linear genotype, derivation, Gads",
• URL = "ftp://ftp.dcs.st-and.ac.uk/pub/norman/GPwCSG.ps.gz",
• URL = "http://hdl.handle.net/10023/14984",
• URL = "https://research-repository.st-andrews.ac.uk/bitstream/10023/14984/2/NormanRPatersonPhDThesis.pdf",
• size = "253 pages",
• abstract = "This thesis presents Genetic Algorithm for Deriving Software (Gads), a new technique for genetic programming. Gads combines a conventional genetic algorithm with a context-sensitive grammar. The key to Gads is the ontogenic mapping, which converts a genome from an array of integers to a correctly typed program in the phenotype language defined by the grammar. A new type of grammar, the reflective attribute grammar (rag), is introduced. The rag is an extension of the conventional attribute grammar, which is designed to produce valid sentences, not to recognise or parse them. Together, Gads and rags provide a scalable solution for evolving type-correct software in independently-chosen context-sensitive languages. The statistics of performance comparison is investigated. A method for representing a set of genetic programming systems or problems on a cladogram is presented. A method for comparing genetic programming systems or problems on a single rational scale is proposed.",
• notes = "Supervisor: Mike Livesey",

}

Genetic Programming entries for Norman R Paterson

Citations