Use this URL to cite or link to this record in EThOS:
Title: Genetic programming with context-sensitive grammars
Author: Paterson, Norman R.
Awarding Body: University of St Andrews
Current Institution: University of St Andrews
Date of Award: 2003
Availability of Full Text:
Access from EThOS:
Access from Institution:
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 onto genic 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 recognize 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.
Supervisor: Livesey, Mike Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: QA76.623P2 ; Genetic programming (Computer science)