PhD thesis,
Genetic programming with context-sensitive grammars
Saint Andrew's University, (September 2002)
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.
