The Evolution of Evolvability in Genetic Programming   [EOE] [GP]

by

Altenberg, L.

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Info: Advances in Genetic Programming, 1994, p. 47-74
Keywords:genetic algorithms, genetic programming
Abstract:
The notion of ``evolvability'' --- the ability of a population to produce variants fitter than any yet existing --- is developed as it applies to genetic algorithms. [GA] A theoretical analysis [TA] of the dynamics of genetic programming [GP] predicts the existence of a novel, emergent selection phenomenon: the evolution [EOE] of evolvability. This is produced by the proliferation, within programs, of blocks of code that have a higher chance of increasing fitness when added to programs. Selection can then come to mold the \em variational aspects of the way evolved programs are represented. A model of code proliferation within programs is analyzed to illustrate this effect. The mathematical and conceptual framework includes: the definition of evolvability as a measure of performance for genetic algorithms; application [GA] of Price's \em Covariance and Selection Theorem to show how the fitness function, representation, [FF] and genetic operators [GO] must interact to produce evolvability --- namely, that genetic operators [GO] produce offspring with fitnesses specifically correlated with their parent's fitnesses; how blocks of code emerge as a new level of replicator, proliferating as a function of their ``constructional fitness'', which is distinct from their schema fitness; and how programs may change from innovative code to conservative code as the populations mature. Several new selection techniques and genetic operators [GO] are proposed in order to give better control over the evolution [EOE] of evolvability and improved evolutionary performance. Copyright 1996 Lee Altenberg
Notes:
Price's Covariance and Selection Theorem 1970 Nature 227 pages 520-521 Fisher's Theorem 1930 "The Genetical Theory of Natural Selection, Clarendon Press, Oxford, UK pages 30-37 Generally better theory for GP -> additional fitness (of blocks) Also known as Altenberg:1994EEGP
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BibTex:
@InCollection{kinnear:altenberg,
  author =       "Lee Altenberg",
  title =        "The Evolution of Evolvability in Genetic Programming",
  booktitle =    "Advances in Genetic Programming",
  publisher =    "MIT Press",
  year =         "1994",
  editor =       "Kenneth E. {Kinnear, Jr.}",
  pages =        "47--74",
  chapter =      "3",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "ftp://ftp.mhpcc.edu/pub/incoming/altenberg/LeeEEGP.ps",
  url_2 =        "http://pueo.mhpcc.edu/~altenber/PAPERS/LeeEEGP.html",
  abstract =     "The notion of ``evolvability'' --- the ability of a
                 population to produce variants fitter than any yet
                 existing --- is developed as it applies to genetic
                 algorithms. A theoretical analysis of the dynamics of
                 genetic programming predicts the existence of a novel,
                 emergent selection phenomenon: the evolution of
                 evolvability. This is produced by the proliferation,
                 within programs, of blocks of code that have a higher
                 chance of increasing fitness when added to programs.
                 Selection can then come to mold the {\em variational}
                 aspects of the way evolved programs are represented. A
                 model of code proliferation within programs is analyzed
                 to illustrate this effect. The mathematical and
                 conceptual framework includes: the definition of
                 evolvability as a measure of performance for genetic
                 algorithms; application of Price's {\em Covariance and
                 Selection Theorem} to show how the fitness function,
                 representation, and genetic operators must interact to
                 produce evolvability --- namely, that genetic operators
                 produce offspring with fitnesses specifically
                 correlated with their parent's fitnesses; how blocks of
                 code emerge as a new level of replicator, proliferating
                 as a function of their ``constructional fitness'',
                 which is distinct from their schema fitness; and how
                 programs may change from innovative code to
                 conservative code as the populations mature. Several
                 new selection techniques and genetic operators are
                 proposed in order to give better control over the
                 evolution of evolvability and improved evolutionary
                 performance.

                 Copyright 1996 Lee Altenberg",
  notes =        "

                 Price's Covariance and Selection Theorem 1970 Nature
                 227 pages 520-521 Fisher's Theorem 1930 {"}The
                 Genetical Theory of Natural Selection, Clarendon Press,
                 Oxford, UK pages 30-37 Generally better theory for GP
                 -> additional fitness (of blocks)

                 Also known as Altenberg:1994EEGP",
  size =         "29 pages",
}