Schema Analysis in Tree-Based Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{burlacu2018schema,

• author = "Bogdan Burlacu and Michael Affenzeller and Michael Kommenda and Gabriel Kronberger and Stephan Winkler",
• title = "Schema Analysis in Tree-Based Genetic Programming",
• booktitle = "Genetic Programming Theory and Practice XV",
• editor = "Wolfgang Banzhaf and Randal S. Olson and William Tozier and Rick Riolo",
• year = "2017",
• pages = "17--37",
• address = "University of Michigan in Ann Arbor, USA",
• month = may # " 18--20",
• organisation = "the Center for the Study of Complex Systems",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-319-90511-2",
• URL = "https://link.springer.com/chapter/10.1007/978-3-319-90512-9_2",
• DOI = "doi:10.1007/978-3-319-90512-9_2",
• abstract = "In this chapter we adopt the concept of schemata from schema theory and use it to analyse population dynamics in genetic programming for symbolic regression. We define schemata as tree-based wild card patterns and we empirically measure their frequencies in the population at each generation. Our methodology consists of two steps: in the first step we generate schemata based on genealogical information about crossover parents and their offspring, according to several possible schema definitions inspired from existing literature. In the second step, we calculate the matching individuals for each schema using a tree pattern matching algorithm. We test our approach on different problem instances and algorithmic flavours and we investigate the effects of different selection mechanisms on the identified schemata and their frequencies.",
• notes = "GPTP 2017, published 2018",

}

Genetic Programming entries for Bogdan Burlacu Michael Affenzeller Michael Kommenda Gabriel Kronberger Stephan M Winkler

Citations