skip to main content
10.1145/1388969.1388999acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
demonstration

Emergent architecture in self organized swarm systems for military applications

Published: 12 July 2008 Publication History

Abstract

Many sectors of the military are interested in Self-Organized (SO) systems because of their flexibility, versatility and economics. The military is researching and employing autonomous and swarming ground robots, Unmanned Aerial Vehicles (UAVs) and Water Vehicles, medical agents, and 'Cyber-craft' security agents. The processes for effectively developing these systems are still in their infancy. Currently, little effort is focused on building simple agent rules with low-level SO systems communication in order to facilitate emergent behaviors. Note that only with the use of effective control structures can the full potential of these systems realized. Presented is an innovative new paradigm for developing SO-based autonomous vehicles. Using a formal design model, the Interactive Partially Observable Markov Decision Process, a full understanding of this SO domain is possible. With this design model and a focused effort on the minimization of computational and informational complexity, emergent entangled control hierarchies allow the SO rules to operate efficiently and effectively. This work extends the formal model decomposition technique, and in doing so ties in the information theoretic optimization to develop emergent structures. Preliminary computational results reflect limited success.

References

[1]
D. J. Nowak, "Exploitation of self organization in uav swarms for optimization in combat environments," Master's thesis, Graduate School of Engineering and Management, Air Force Institute of Technology (AU), Wright-Patterson AFB, OH, March 2008.
[2]
S. Camazine, Self Organization in Biological Systems. USA: Princeton University Press, 2003.
[3]
R. Cottam, W. Ranson, and R. Vounckx, "Autocreative hierarchy ii: dynamics self-organization, emergence and level-changing," in Integration of Knowledge Intensive Multi-Agent Systems, 2003. International Conference on, 30 Sept.-4 Oct. 2003, pp. 766--773.
[4]
F. Heylighen and C. Joslyn, "Cybernetics and second-order cybernetics," Encyclopedia of Physical Science & Technology, vol. 3rd ed., 2001, academic Press, New York.
[5]
E. e. a. Bonabeau, Swarm Intelligence: From Natural to Artificial Systems. Sante Fe Institute, 1999, new York.
[6]
F. Heylighen, "Self-organization and complexity in the natural sciences," Principia Cybernetica Web, Dec 2006. {Online}. Available: http://pespmc1.vub.ac.be/COMPNATS.HTML
[7]
W. L. Sheridan, Thomas B. ; Verplank, "Human and computer control of undersea teleoperators," Massachusetts Institute of Technology Cambridge Man-Machine Systems Lab, Technical rept., JUL 1978, aDA057655.
[8]
V. Braitenburg, Vehicles: Experiments in Synthetic Psychology, E. C. T. e. a. Walker, Ed. Bradford Books, 1987.
[9]
R. A. Brooks, "A robust layered control system for a mobile robot," IEEE JOURNAL OF ROBOTICS AND AUTOMATION, vol. RA-2, pp. 14--23, 1986.
[10]
E. Gat, "On three-layer architectures," in Artificial Intelligence and Mobile Robots, R. P. B. D. Kortenkamp and e. R. Murphy, Eds. MIT/AAAI Press, 1997.
[11]
I. C. Price, "Evolving self organizing behavior for homogeneous and heterogeneous swarms of uavs and ucavs,"Master's thesis, Graduate School of Engineering and Management, Air Force Institute of Technology (AU), Wright-Patterson AFB, OH, March 2006.
[12]
J. K. Rosenblatt, "DAMN: A distributed architecture for mobile navigation," in Proc. of the AAAI Spring Symp. on Lessons Learned from Implemented Software Architectures for Physical Agents, Stanford, CA, 1997. {Online}. Available:citeseer.ist.psu.edu/article/rosenblatt97damn.html
[13]
C. W. Reynolds, "Steering behaviors for autonomous characters," in Proceedings of the 2005 Winter Simulation Conference. San Jose, California, 2005, pp. 763--782.
[14]
I. P. Dustin J Nowak and G. B. Lamont, "Self organized uav swarm planning optimization for search and destroy using swarmfare simulation," in Proceedings of the 2007 Winter Simulation Conference, M.-H. H. J. S. J. D. T. S. G. Henderson, B. Biller and e. R. R. Barton, Eds., 2007.
[15]
H. Haken, Information and Self Organization. Germany: Springer, 2003.
[16]
J. H. Holland, Hidden Order: How Adaptation Builds Complexity. Addison-Wesley, 1996, new York.
[17]
F. B. M. Prokopenko and A. J. Ryan, "An information-theoretic primer on complexity, self-organisation and emergence," Advances in Complex Systems, 2007.
[18]
P. Gmytrasiewicz and P. Doshi, "Interactive pomdps: Properties and preliminary results," 2004. {Online}. Available: citeseer.ist.psu.edu/gmytrasiewicz04interactive.html
[19]
D. Nowak, "Cybercraft swarm intelligence," Air Force Institute of Technology, Tech. Rep., 2008.

Cited By

View all
  • (2021)Self-Adaptive Software Systems in Contested and Resource-Constrained Environments: Overview and ChallengesIEEE Access10.1109/ACCESS.2020.30434409(10711-10728)Online publication date: 2021
  • (2017)Scalability in Self-Organizing Systems: An Experimental Case Study on Foraging SystemsDisciplinary Convergence in Systems Engineering Research10.1007/978-3-319-62217-0_38(543-557)Online publication date: 26-Nov-2017
  • (2009)Collaborative Mission Planning & Autonomous Control Technology (CoMPACT) System Employing Swarms of UAVsAIAA Guidance, Navigation, and Control Conference10.2514/6.2009-5653Online publication date: 14-Jun-2009

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
GECCO '08: Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
July 2008
1182 pages
ISBN:9781605581316
DOI:10.1145/1388969
  • Conference Chair:
  • Conor Ryan,
  • Editor:
  • Maarten Keijzer
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 July 2008

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. agents
  2. autonomous
  3. self-organization
  4. swarm intelligence

Qualifiers

  • Demonstration

Conference

GECCO08
Sponsor:

Acceptance Rates

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 15 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2021)Self-Adaptive Software Systems in Contested and Resource-Constrained Environments: Overview and ChallengesIEEE Access10.1109/ACCESS.2020.30434409(10711-10728)Online publication date: 2021
  • (2017)Scalability in Self-Organizing Systems: An Experimental Case Study on Foraging SystemsDisciplinary Convergence in Systems Engineering Research10.1007/978-3-319-62217-0_38(543-557)Online publication date: 26-Nov-2017
  • (2009)Collaborative Mission Planning & Autonomous Control Technology (CoMPACT) System Employing Swarms of UAVsAIAA Guidance, Navigation, and Control Conference10.2514/6.2009-5653Online publication date: 14-Jun-2009

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media