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Genetic Programming Theory and Practice III pp 15–32Cite as

Evolving Swarming Agents in Real Time

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Part of the book series: Genetic Programming ((GPEM,volume 9))

Abstract

An important application for population search methods (such as particle swarm optimization and the several varieties of synthetic evolution) is the engineering problem of configuring individual agents to yield useful emergent behavior. While the biological antecedents of population-based search operate in real time, most engineered versions run off-line. For some applications, it is desirable to evolve agents as they are running in the system that they support. We describe two instances of such systems that we have developed and highlight lessons learned.

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References

  • Agah, A. and Bekey, G.A. (1996). A genetic algorithm-based controller for decentralized multi-agent robotic systems. In The 1996 IEEE International Conf. on Evolutionary Computation, pages 431–436, Nagoya, Japan. IEEE.

    Google Scholar 

  • Booker, L. B., Goldberg, D. E., and Holland, J. H. (1989). Classifier systems and genetic algorithms. Artificial Intelligence, 40:235–282.

    Article  Google Scholar 

  • Botee, Hozefa M. and Bonabeau, Eric (1998). Evolving ant colony optimization. Adv. Complex Systems, 1:149–159.

    Article  Google Scholar 

  • Boumaza, Amine M. and Louchet, Jean (2001). Dynamic flies: Using real-time parisian evolution in robotics. In Boers, Egbert J. W., Cagnoni, Stefano, Gottlieb, Jens, Hart, Emma, Lanzi, Pier Luca, Raidl, Gunther R., Smith, Robert E., and Tijink, Harald, editors, Applications of Evolutionary Computing, volume 2037 of LNCS, pages 288–297, Lake Como, Italy. Springer-Verlag.

    Google Scholar 

  • Brooks, Rodney A. (1992). Artificial life and real robots. In Varela, Francisco J. and Bourgine, Paul, editors, The First European Conference on Artificial Life, pages 3–10.

    Google Scholar 

  • Brueckner, Sven (2000). Return from the Ant: Synthetic Ecosystems for Manufacturing Control. Dr.rer.nat., Humboldt University Berlin.

    Google Scholar 

  • Brueckner, Sven A. and Parunak, H. Van Dyke (2004). Swarming distributed pattern detection and classification. In Weyns, Danny, Parunak, H. Van Dyke, and Michel, Fabien, editors, Workshop on Environments for Multi-Agent Systems (E4MAS 2004), volume LNAI 3374, New York, NY. Springer.

    Google Scholar 

  • Corne, D., Dorigo, M., and Glover, F., editors (1999). New Ideas in Optimisation. McGraw-Hill, New York.

    Google Scholar 

  • Dadone, P. and VanLandingham, H.F. (1999). Adaptive online parameter tuning using genetic algorithms. In Proceedings of WSC4: 4th Online World Conference on Soft Computing in Industrial Applications.

    Google Scholar 

  • Forrest, S., Hofmeyr, S., and Somayaji, A. (1997). Computer immunology. Communications of the ACM, 40:88–96.

    Article  Google Scholar 

  • Harvey, I., Husbands, P., and Cliff, D. (1992). Issues in evolutionary robotics. In Meyer, J-A, Roitblat, H, and Wilson, S, editors, The Second International Conference on Simulation of Adaptive Behaviour (SAB92), pages 364–373.

    Google Scholar 

  • Kantz, Holger and Schreiber, Thomas (1997). Nonlinear Time Series Analysis. Cambridge Nonlinear Science Series. Cambridge University Press, Cambridge, UK.

    Google Scholar 

  • Li, Yi, Riolo, Rick, and Savit, Robert (2000a). Evolution in minority games. i. games with a fixed strategy space. Physica A, 2000(276):234–264.

    Article  MathSciNet  Google Scholar 

  • Li, Yi, Riolo, Rick, and Savit, Robert (2000b). Evolution in minority games ii. games with variable strategy spaces. Physica A, 2000(276):265–283.

    Article  MathSciNet  Google Scholar 

  • Nordin, P. and Banzhaf, W. (1997). Real time control of a khepera robot using genetic programming. Cybernetics and Control, 26(3):533–561.

    MathSciNet  Google Scholar 

  • Ortony, A., Clore, G.L., and Collins, A. (1988). The cognitive structure of emotions. Cambridge University Press, Cambridge, UK.

    Google Scholar 

  • Panait, Liviu A. and Luke, Sean (2004). Learning ant foraging behaviours. In Pollack, Jordan, Bedau, Mark, Husbands, Phil, Ikegami, Takashi, and Watson, Richard A., editors, Artificial Life XI Ninth International Conference on the Simulation and Synthesis of Living Systems, pages 575–580, Boston, Massachusetts. The MIT Press.

    Google Scholar 

  • Parunak, H. Van Dyke, Bisson, Robert, Brueckner, Sven, Matthews, Robert, and Sauter, John (2005). Representing dispositions and emotions in simulated combat. In Thompson, Simon, Ghanea-Hercock, Robert, Greaves, Mark, Meyer, Andre, and Jennings, Nick, editors, Workshop on Defence Applications of Multi-Agent Systems (DAMAS05, at AAMAS05), page (forthcoming), Utrecht, Netherlands.

    Google Scholar 

  • Parunak, H. Van Dyke and Brueckner, Sven (2003). Swarming coordination of multiple UAV’s for collaborative sensing. In Second AIAA “Unmanned Unlimited” Systems, Technologies, and Operations Conference, San Diego, CA. AIAA.

    Google Scholar 

  • Parunak, H. Van Dyke, Purcell, Michael, and O’Connell, Robert (2002). Digital pheromones for autonomous coordination of swarming UAV’s. In First AIAA Unmanned Aerospace Vehicles, Systems, Technologies, and Operations Conference, Norfolk, VA. AIAA.

    Google Scholar 

  • Quinn, M. (2001). Evolving communication without dedicated communication channels. In Kelemen, J. and Sosik, P., editors, Advances in Artificial Life: Sixth European Conference on Artificial Life: ECAL2001, pages 357–366, Prague, Czech Republic. Springer.

    Google Scholar 

  • Reynolds, Craig W. (1987). Flocks, herds, and schools: A distributed behavioral model. Computer Graphics, 21(4):25–34.

    MathSciNet  Google Scholar 

  • Riolo, Rick L, Axelrod, Robert, and Cohen, Michael D. (2001). Evolution of cooperation without reciprocity. Nature, 414(22 Nov):441–443.

    Article  Google Scholar 

  • Sauter, John A., Matthews, Robert, Parunak, H. Van Dyke, and Brueckner, Sven (2002). Evolving adaptive pheromone path planning mechanisms. In Autonomous Agents and Multi-Agent Systems (AAMAS02), pages 434–440, Bologna, Italy.

    Google Scholar 

  • Sauter, John A., Matthews, Robert, Parunak, H. Van Dyke, and Brueckner, Sven A. (2005). Performance of digital pheromones for swarming vehicle control. In Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems, page (forthcoming), Utrecht, Netherlands.

    Google Scholar 

  • Savit, Robert, Brueckner, Sven A., Parunak, H. Van Dyke, and Sauter, John (2002). Phase structure of resource allocation games. Physics Letters A, 311:359–364.

    Article  Google Scholar 

  • Spector, Lee, Klein, Jon, Perry, Chris, and Feinstein, Mark (2005). Emergence of collective behavior in evolving populations of flying agents. Genetic Programming and Evolvable Machines, 6. Prepublication Date: 6 August 2004.

    Google Scholar 

  • Steels, L. (2000). The puzzle of language evolution. Kognitionswissenschaft, 8(4):143–150.

    Article  Google Scholar 

  • Weinstein, Peter, Parunak, H. Van Dyke, Chiusano, Paul, and Brueckner, Sven (2004). Agents swarming in semantic spaces to corroborate hypotheses. In AAMAS 2004, pages 1488–1489, New York, NY.

    Google Scholar 

  • Weyns, Danny, Parunak, H. Van Dyke, Michel, Fabien, Holvoet, Tom, and Ferber, Jacques (2004). Multiagent systems, state-of-the-art and research challenges. In Weyns, Danny, Parunak, H. Van Dyke, and Michel, Fabien, editors, Workshop on Environments for Multi-Agent Systems (E4MAS 2004), volume LNAI 3374, New York, NY. Springer.

    Google Scholar 

  • White, Tony, Pagurek, Bernard, and Oppacher, Franz (1998). ASGA: Improving the ant system by integration with genetic algorithms. In Koza, John R., Banzhaf, Wolfgang, Chellapilla, Kumar, Deb, Kalyanmoy, Dorigo, Marco, Fogel, David B., Garzon, Max H., Goldberg, David E., Iba, Hitoshi, and Riolo, Rick, editors, Genetic Programming 1998: Proceedings of the Third Annual Conference, pages 610–617, University of Wisconsin, Madison, Wisconsin, USA. Morgan Kaufmann.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Altarum Institute, USA

    H. Van Dyke Parunak

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  1. H. Van Dyke Parunak
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Editor information

Editors and Affiliations

  1. Chevron Information Technology Company, USA

    Tina Yu

  2. Center for the Study of Complex Systems, University of Michigan, USA

    Rick Riolo

  3. Genetics Squared, Inc., USA

    Bill Worzel

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© 2006 Springer Science+Business Media, Inc.

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Parunak, H.V.D. (2006). Evolving Swarming Agents in Real Time. In: Yu, T., Riolo, R., Worzel, B. (eds) Genetic Programming Theory and Practice III. Genetic Programming, vol 9. Springer, Boston, MA. https://doi.org/10.1007/0-387-28111-8_2

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  • DOI: https://doi.org/10.1007/0-387-28111-8_2

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-0-387-28110-0

  • Online ISBN: 978-0-387-28111-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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