Evolving gene expression to reconfigure analogue devices

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Kester Dean Clegg",
  title =        "Evolving gene expression to reconfigure analogue
  school =       "University of York",
  year =         "2008",
  month =        May,
  keywords =     "genetic algorithms, genetic programming, Cartesian
                 genetic programming",
  URL =          "http://www-users.cs.york.ac.uk/susan/teach/theses/clegg.htm",
  URL =          "http://www.cs.york.ac.uk/ftpdir/reports/2008/YCST/05/YCST-2008-05.pdf",
  size =         "203 pages",
  abstract =     "Repeated, morphological functionality, from limbs to
                 leaves, is widespread in nature. Pattern formation in
                 early embryo development has shed light on how and why
                 the same genes are expressed in different locations or
                 at different times. Practitioners working in
                 evolutionary computation have long regarded nature's
                 reuse of modular functionality with admiration. But
                 repeating nature's trick has proven difficult. To date,
                 no one has managed to evolve the design for a car, a
                 house or a plane. Or indeed anything where the number
                 of interdependent parts exposed to random mutation is
                 large. It seems that while we can use evolutionary
                 algorithms for search-based optimisation with great
                 success, we cannot use them to tackle large, complex
                 designs where functional reuse is essential. This
                 thesis argues that the modular functionality provided
                 by gene reuse could play an important part in
                 evolutionary computation being able to scale, and that
                 by expressing subsets of genes in specific contexts,
                 successive stages of phenotype configuration can be
                 controlled by evolutionary search. We present a
                 conceptual model of context-specific gene expression
                 and show how a genome representation can hold many
                 genes, only a few of which need be expressed in a
                 solution. As genes are expressed in different contexts,
                 their functional role in a solution changes. By
                 allowing gene expression to discover phenotype
                 solutions, evolutionary search can guide itself across
                 multiple search domains. The work here describes the
                 design and implementation of a prototype system to
                 demonstrates the above features and evolve genomes that
                 are able to use gene expression to find and deploy
                 solutions, permitting mechanisms of dynamic control to
                 be discovered by evolutionary computation.",

Genetic Programming entries for Kester Clegg