Emergence of Collective Behavior in Evolving
Populations of Flying Agents

This page contains material related to "Emergence of Collective Behavior in Evolving Populations of Flying Agents," a paper in the Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003), published by Springer-Verlag (LNCS series Homepage: http://www.springer.de/comp/lncs/index.html).

This paper won the Best Paper Award for the AAAA track (A-Life, Adaptive Behavior, Agents, and Ant Colony Optimization) at GECCO-2003.

Abstract

We demonstrate the emergence of collective behavior in two evolutionary computation systems, one an evolutionary extension of a classic (highly constrained) flocking algorithm and the other a relatively un-constrained system in which the behavior of agents is governed by evolved computer programs. We describe the systems in detail, document the emergence of collective behavior, and argue that these systems present new opportunities for the study of group dynamics in an evolutionary context.

Citation

Spector, L., J. Klein, C. Perry, and M. Feinstein. 2003. Emergence of Collective Behavior in Evolving Populations of Flying Agents. In E. Cantu-Paz, J.A. Foster, K. Deb, L.D. Davis, R. Roy, U.-M. O'Reilly, H.-G. Beyer, R. Standish, G. Kendall, S. Wilson, M. Harman, J. Wegener, D. Dasgupta. M.A. Potter, A.C. Schultz, K.A. Dowsland, N. Jonoska, J. Miller (Eds.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2003). Berlin: Springer-Verlag. pp. 61-73.

Full paper

Note: This paper is © Springer-Verlag (LNCS series Homepage: http://www.springer.de/comp/lncs/index.html).

Full paper in PDF format: http://hampshire.edu/lspector/pubs/spector-gecco2003.pdf (1.1MB).

Expanded version of the paper

An expanded version of the paper was published in the journal Genetic Programming and Evolvable Machines:

Spector, L., J. Klein, C. Perry, and M. Feinstein. 2005. Emergence of Collective Behavior in Evolving Populations of Flying Agents. In Genetic Programming and Evolvable Machines, Vol. 6, No. 1, pp. 111-125. (pdf 254KB)

Associated links

• The BREVE simulation environment: http://www.spiderland.org/breve.
• The Push programming language for evolutionary computation (used to encode agent behaviors in SwarmEvolve 2.0) and related documentation: http://hampshire.edu/lspector/push.html.
• SwarmEvolve 1.0:
  • SwarmEvolve 1.0 source code: http://hampshire.edu/lspector/swarmevolve-1.0.tz.
  • A typical SwarmEvolve 1.0 action sequence: http://hampshire.edu/lspector/swarmevolve-ex1.mov (~10MB).
  • A SwarmEvolve 1.0 action sequence demonstrating evolved species-specific strategies; the purple species is exhibiting collective or multicellular organization: http://hampshire.edu/lspector/swarmevolve-ex2.mov (~20MB).
  • A SwarmEvolve1.0 action sequence demonstrating genetic drift (note the behavior of the blue agents): http://hampshire.edu/lspector/swarmevolve-ex3.mov (~10MB).
• SwarmEvolve 2.0:
  • SwarmEvolve 2.0 source code: http://hampshire.edu/lspector/swarmevolve-2.0.tz. To run the system on current versions of BREVE you will also need the Push interpreter plugin and other files; the full package is available at http://hampshire.edu/lspector/swarmevolve2push.tgz.
  • A SwarmEvolve 2.0 action sequence demonstrating evolutionary activity (note the increase in the number of red agents): http://hampshire.edu/lspector/swarmevolve2-ex1.mov (~15MB).
  • A SwarmEvolve 2.0 action sequence demonstrating the emergence of reproductive competence. In the first half of this clip, as in the beginning of all SwarmEvolve 2.0 runs, "spontaneous generation" is required to sustain the population. Near the middle of this clip a reproductively competent sub-population emerges and takes over the population. From this point onward the population is self-sustaining and natural selection acts to evolve adaptive behaviors. (This is the same run as was used to produce the "evolutionary activity" clip above.): http://hampshire.edu/lspector/swarmevolve2-ex0.mov (~15MB).