- author = "David R. White and Benjamin Fowler and Wolfgang Banzhaf and Earl T. Barr",
- title = "Modelling Genetic Programming as a Simple Sampling Algorithm",
- booktitle = "Genetic Programming Theory and Practice XVII",
- year = "2019",
- editor = "Wolfgang Banzhaf and Erik Goodman and Leigh Sheneman and Leonardo Trujillo and Bill Worzel",
- pages = "367--381",
- address = "East Lansing, MI, USA",
- month = "16-19 " # may,
- publisher = "Springer",
- keywords = "genetic algorithms, genetic programming, Schema theory, Convergence, Covariance, Price's theorem",
- isbn13 = "978-3-030-39957-3",
-
URL = "
http://www.cs.mun.ca/~banzhaf/papers/GPTP_2019_White_2020.pdf",
-
DOI = "
10.1007/978-3-030-39958-0_18",
- size = "15 pages",
- abstract = "This chapter proposes a new model of tree-based Genetic Programming (GP) as a simple sampling algorithm that samples minimal schemata (subsets of the solution space) described by a single concrete node at a single position in the expression tree. We show that GP explores these schemata in the same way across three benchmarks, rapidly converging the population to a specific function at each position throughout the upper layers of the expression tree. This convergence is driven by covariance between membership of a simple schema and rank fitness. We model this process using Prices theorem \cite{price:nature} and provide empirical evidence to support our model. The chapter closes with an outline of a modification of the standard GP algorithm that reinforces this bias by converging populations to fit schemata in an accelerated way.",
-
notes = "Keijzer-6 sqrt. Korns-12, Vladislavleva-4
Part of \cite{Banzhaf:2019:GPTP}, published after the workshop",
