Visualizing evolutionary dynamics of self-replicators using graph-based genealogy

Chris Salzberg, Antony Antony, Hiroki Sayama

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

3 Citations (Scopus)

Abstract

We present a general method for evaluating and visualizing evolutionary dynamics of self-replicators using a graph-based representation for genealogy. Through a transformation from the space of species and mutations to the space of nodes and links, evolutionary dynamics are understood as a flow in graph space. Mapping functions are introduced to translate graph nodes to points in an n-dimensional visualization space for interpretation and analysis. Using this scheme, we evaluate the effect of a dynamic environment on a population of self-reproducing loops. Resulting images visually reveal the critical role played by genealogical graph space partitioning in the evolutionary process.

Original languageEnglish
Title of host publicationAdvances in Artificial Life
EditorsWolfgang Banzhaf, Jens Ziegler, Thomas Christaller, Peter Dittrich, Jan T. Kim
PublisherSpringer Verlag
Pages387-394
Number of pages8
ISBN (Print)3540200576, 9783540200574
Publication statusPublished - 2003 Jan 1
Externally publishedYes
Event7th European Conference on Artificial Life, ECAL 2003 - Dortmund, Germany
Duration: 2003 Sep 142003 Sep 17

Publication series

NameLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2801
ISSN (Print)0302-9743

Other

Other7th European Conference on Artificial Life, ECAL 2003
CountryGermany
CityDortmund
Period03/9/1403/9/17

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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