Introducing Graphical Models to Analyze Genetic Programming Dynamics

Created by W.Langdon from gp-bibliography.bib Revision:1.8620

@InProceedings{Hemberg:2013:foga,

• author = "Erik Hemberg and Kalyan Veeramachaneni and Constantin Berzan and Una-May O'Reilly",
• title = "Introducing Graphical Models to Analyze Genetic Programming Dynamics",
• booktitle = "Foundations of Genetic Algorithms",
• year = "2013",
• editor = "Frank Neumann and Kenneth {De Jong}",
• pages = "75--86",
• address = "Adelaide, Australia",
• month = "16-20 " # jan,
• organisation = "SigEvo",
• publisher = "ACM",
• keywords = "genetic algorithms, genetic programming, Bayesian networks, graphical models",
• isbn13 = "978-1-4503-1990-4",
• URL = "http://doi.acm.org/10.1145/2460239.2460247",
• DOI = "10.1145/2460239.2460247",
• acmid = "2460247",
• size = "12 pages",
• abstract = "We propose graphical models as a new means of understanding genetic programming dynamics. Herein, we describe how to build an unbiased graphical model from a population of genetic programming trees. Graphical models both express information about the conditional dependency relations among a set of random variables and they support probabilistic inference regarding the likelihood of a random variable's outcome. We focus on the former information: by their structure, graphical models reveal structural dependencies between the nodes of genetic programming trees. We identify graphical model properties of potential interest in this regard - edge quantity and dependency among nodes expressed in terms of family relations. Using a simple symbolic regression problem we generate a graphical model of the population each generation. Then we interpret the graphical models with respect to conventional knowledge about the influence of subtree crossover and mutation upon tree structure.",
• notes = "Also known as \cite{Hemberg:2013:IGM:2460239.2460247} http://www.sigevo.org/foga-2013/index.html",

}

Genetic Programming entries for Erik Hemberg Kalyan Veeramachaneni Constantin Berzan Una-May O'Reilly

Citations