A case study of the de novo evolution of a complex odometric behavior in digital organisms

PLoS One. 2013;8(4):e60466. doi: 10.1371/journal.pone.0060466. Epub 2013 Apr 8.

Abstract

Investigating the evolution of animal behavior is difficult. The fossil record leaves few clues that would allow us to recapitulate the path that evolution took to build a complex behavior, and the large population sizes and long time scales required prevent us from re-evolving such behaviors in a laboratory setting. We present results of a study in which digital organisms-self-replicating computer programs that are subject to mutations and selection-evolved in different environments that required information about past experience for fitness-enhancing behavioral decisions. One population evolved a mechanism for step-counting, a surprisingly complex odometric behavior that was only indirectly related to enhancing fitness. We examine in detail the operation of the evolved mechanism and the evolutionary transitions that produced this striking example of a complex behavior.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Behavior, Animal*
  • Computer Simulation*
  • Evolution, Molecular*
  • Genome
  • User-Computer Interface

Grants and funding

Funding was provided by the National Science Foundation, http://www.nsf.gov/, NSF grants CCF-0643952 and DBI-0939454; and the Cambridge Templeton Consortium, http://www.cambridge-templetonconsortium.org/, "Emerging Intelligence: Contingency, Convergence and Constraints in the Evolution of Intelligent Behavior." The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.