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The Evolution of Evolvability in Genetic Programming 1 Lee Altenberg
 

Summary: 1
The Evolution of Evolvability in Genetic Programming 1
Lee Altenberg
Institute of Statistics and Decision Sciences, Duke University
Durham, NC 27708-0251 Internet: altenber@acpub.duke.edu
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 selectionphenomenon: 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
variational aspectsof 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 asa measureof performance for genetic algorithms;application of Price's
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.

  

Source: Altenberg, Lee - Department of Information and Computer Science, University of Hawai'i at Manoa

 

Collections: Computer Technologies and Information Sciences