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JACIII Vol.14 No.6 pp. 574-580
doi: 10.20965/jaciii.2010.p0574
(2010)

Paper:

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Task Allocation in Multistate Systems

Tsuyoshi Mizuguchi*1,*2, Ken Sugawara*3,
and Toshiya Kazama*4

*1Department of Mathematical Sciences, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai 599-8531, Japan

*2PRESTO, Japan Science and Technology Agency (JST), 4-1-8 Honcho Kawaguchi, Saitama 332-0012, Japan

*3Department of Information Science, Tohoku Gakuin University, 2-1-1 Tenjinzawa, Izumi-ku, Sendai 981-3193, Japan

*4Department of Mathematical and Life Sciences, Hiroshima University, 1-3-1 Kagami-yama, Higashi-Hiroshima 739-8526, Japan

Received:
November 30, 2009
Accepted:
May 13, 2010
Published:
September 20, 2010
Creative Commons License
Keywords:
robust and stochastic optimization, interacting agent model, stock material
Abstract
Multistate task allocation inspired by social-insect polyethism is treated from the viewpoint of proportionally regulating a population between different states, i.e., the system is homeostatic against external disturbance and environmental change. Using a dynamical model consisting of identical elements and external variable “stock materials,” adaptability to external disturbances is studied numerically. Experiments are performed with actual robots moving in virtual pheromone fields simulated by computer graphics and video camera feedback demonstrating task allocation.
Cite this article as:
T. Mizuguchi, K. Sugawara, and T. Kazama, “Task Allocation in Multistate Systems,” J. Adv. Comput. Intell. Intell. Inform., Vol.14 No.6, pp. 574-580, 2010.
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References
  1. [1] E. O. Wilson, “The Insect Societies,” Oxford Univ. Press, 1971.
  2. [2] K. B. Raper and J. Elisha, “Pseudoplasmodium formation and organization in Dictyostelium discoideum,” Mitchell Scient. Soc., Vol.56, pp. 241-282, 1940.
  3. [3] J. T. Bonner, “A theory of the control of differentiation in the cellular slime molds,” Q. Rev. Biol., Vol.32, pp. 232-246, 1957; “The Cellular Slime Molds,” Princeton Univ. Press, 1967.
  4. [4] W. F. Loin’s, “Dictyostelium discoideum: A developmental System,” Academic Press, 1975.
  5. [5] M. Oyama, K. Okamoto, and I. Takeuchi, “Proportion regulation without pattern formation in Dictyostelium discoideum,” J. Embryol. Exp. Morph., Vol.75, pp. 293-301, 1983.
  6. [6] S. N. Beshers and J. H. Fewell, “MODELS OF DIVISION OF LABOR IN SOCIAL INSECTS,” Annu. Rev. Entomol., Vol.46, pp. 413-440, 2001.
  7. [7] E. Bonabeau, M. Dorigo, and G. Theraulaz, “Swarm Intelligence,” Oxford University press, 1999.
  8. [8] C. Tofts, “Algorithms for task allocation in ants (a study of temporal polyethism: theory),” Bull. Math. Biol., Vol.55, pp. 891-918, 1993.
  9. [9] T. Mizuguchi and M. Sano, “Proportion Regulation of Biological Cells in Globally Coupled Nonlinear Systems,” Phys. Rev. Lett., Vol.75, pp. 966-969, 1995.
  10. [10] L. E. Parker, “Distributed Intelligence: Overview of the Field and its Application in Multi-Robot Systems,” J. of Physical Agents, Vol.2 No.1, pp. 5-14, 2008.
  11. [11] T. Mizuguchi and K. Sugawara, “Proportion regulation in task allocation systems,” IEICE Trans. Fundamentals , Vol.E89-A, No.10, pp. 2745-2751, 2006.
  12. [12] J. Svennebring and S. Koenig, “Building Terrain-Covering Ant Robots,” Autonomous Robots, No.16, No.3, pp. 313-332, 2004.
  13. [13] S. Nouyan, R. Gros, M. Bonani, F. Mondada, and M. Dorigo, “Teamwork in Self-Organized Robot Colonies,” IEEE Trans. on Evolutionary Computation, Vol.13, No.4, pp. 695-711, 2009.
  14. [14] A. T. Hayes, A. Martinoli, and R. M. Goodman, “Distributed Odor Source Localization,” IEEE Sensors, Vol.2, No.3, pp. 260-271, 2002.
  15. [15] R. Fujisawa, H. Imamura, T. Hashimoto and F. Matsuno, “Dependency by Concentration of Pheromone Trail for Multiple Robots,” Proc. of 6th Int. Conf. on Ant Colony Optimization and Swarm Intelligence, pp. 283-290, 2008.
  16. [16] A. H. Purnamadjaja and R. A. Russell, “Bi-directional pheromone communication between robots,” Robotica, Vol.28, pp. 69-79, 2010.
  17. [17] T. Kazama, K. Sugawara and T. Watanabe, “Collecting Behavior of Interacting Robots with Virtual Pheromone,” Proc. 7th Int. Symp. on Distributed Autonomous Robotic Systems pp. 331-340, 2004.

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