Visualization of Genetic Lineages and Inheritance Information in Genetic Programming

Research output: Chapter in Book/Report/Conference proceedingsConference contribution

14 Citations (Scopus)

Abstract

Many studies emphasize the importance of genetic diversity and the need for an appropriate tuning of selection pressure in genetic programming. Additional important aspects are the performance and effects of the genetic operators (crossover and mutation) on the transfer and stabilization of inherited information blocks during the run of the algorithm. In this context, different ideas about the usage of lineage and genealogical information for improving genetic programming have taken shape in the last decade. Our work builds on those ideas by introducing an evolution tracking framework for assembling genealogical and inheritance graphs of populations. The proposed approach allows detailed investigation of phenomena related to building blocks, size evolution, ancestry and diversity. We introduce the notion of genetic fragments to represent subtrees that are affected by reproductive operators (mutation and crossover) and present a methodology for tracking such fragments using flexible similarity measures. A fragment matching algorithm was designed to work on both structural and semantic levels, allowing us to gain insight into the exploratory and exploitative behavior of the evolutionary process. The visualization part which is the subject of this paper integrates with the framework and provides an easy way of exploring the population history. The paper focuses on a case study in which we investigate the evolution of a solution to a symbolic regression benchmark problem.

Original languageEnglish
Title of host publicationGECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion
PublisherACM Sigevo
Pages1351-1358
Number of pages8
ISBN (Print)9781450319645
DOIs
Publication statusPublished - 2013
EventGenetic and Evolutionary Computation Conference - Amsterdam, Netherlands
Duration: 6 Jul 201310 Jul 2013

Publication series

NameGECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference Companion

Conference

ConferenceGenetic and Evolutionary Computation Conference
CountryNetherlands
CityAmsterdam
Period06.07.201310.07.2013

Keywords

  • Algorithm analysis
  • Genetic programming
  • Population genealogy
  • Visualization

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