Evolving digital ecological networks

PLoS Comput Biol. 2013;9(3):e1002928. doi: 10.1371/journal.pcbi.1002928. Epub 2013 Mar 7.

Abstract

"It is hard to realize that the living world as we know it is just one among many possibilities" [1]. Evolving digital ecological networks are webs of interacting, self-replicating, and evolving computer programs (i.e., digital organisms) that experience the same major ecological interactions as biological organisms (e.g., competition, predation, parasitism, and mutualism). Despite being computational, these programs evolve quickly in an open-ended way, and starting from only one or two ancestral organisms, the formation of ecological networks can be observed in real-time by tracking interactions between the constantly evolving organism phenotypes. These phenotypes may be defined by combinations of logical computations (hereafter tasks) that digital organisms perform and by expressed behaviors that have evolved. The types and outcomes of interactions between phenotypes are determined by task overlap for logic-defined phenotypes and by responses to encounters in the case of behavioral phenotypes. Biologists use these evolving networks to study active and fundamental topics within evolutionary ecology (e.g., the extent to which the architecture of multispecies networks shape coevolutionary outcomes, and the processes involved).

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Animals
  • Biological Evolution*
  • Computational Biology*
  • Computer Simulation
  • Ecology*
  • Genome
  • Host-Parasite Interactions
  • Models, Biological*
  • Plants
  • Symbiosis

Grants and funding

This work was funded by a Marie Curie International Outgoing Fellowship within the European Commision's 7th Framework Programme (to MAF), an AT&T Research Labs Fellowship (to LZ), and funding from the BEACON Center and iCER (to APW and CO). This material is based in part upon work supported by the National Science Foundation under Cooperative Agreement No. DBI-0939454. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The funders had no role in the preparation of the manuscript.