Complexity Drift in Evolutionary Computation with Tree Representations

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@TechReport{rosca:1996:cdectr,

• author = "Justinian P. Rosca and Dana H. Ballard",
• title = "Complexity Drift in Evolutionary Computation with Tree Representations",
• institution = "University of Rochester, Computer Science Department",
• year = "1996",
• type = "Technical Report",
• number = "NRL5",
• address = "Rochester, NY, USA",
• month = dec,
• keywords = "genetic algorithms, genetic programming",
• URL = "ftp://ftp.cs.rochester.edu/pub/u/rosca/gp/96.drift.ps.gz",
• abstract = "One serious problem of standard Genetic Programming (GP) is that evolved expressions appear to drift towards large and slow forms on average. This report presents a novel analysis of the role played by variable complexity in the selection and survival of GP expressions. It defines a particular property of GP representations, called {\it rooted tree-schema}, that sheds light on the role of variable complexity of evolved representations. A tree-schema is a relation on the space of tree-shaped structures which provides a quantifiable partitioning of the search space. The present analysis answers questions such as: What role does variable complexity play in the selection and survival of evolved expressions? What is the influence of a parsimony penalty? How heavy should parsimony penalty be weighted or how should it be adapted in order to preserve the underlying optimization process? Are there alternative approaches to simulating a parsimony penalty that do not result in a change of the fitness landscape? The present report provides theoretical answers to these questions, interpretation of these results, and an experimental perspective.",
• notes = "Section 2 Schemata Theory",
• size = "30 pages",

}

Genetic Programming entries for Justinian Rosca Dana H Ballard

Citations