Abstract
This paper considers an anisotropic swarm model that consists of a group of mobile autonomous agents with an attraction-repulsion function that can guarantee collision avoidance between agents and a Gaussian-type attractant/repellent nutrient profile. The swarm behavior is a result of a balance between inter-individual interplays as well as the interplays of the swarm individuals (agents) with their environment. It is proved that the members of a reciprocal swarm will aggregate and eventually form a cohesive cluster of finite size. It is shown that the swarm system is completely stable, that is, every solution converges to the equilibrium point set of the system. Moreover, it is also shown that all the swarm individuals will converge to more favorable areas of the Gaussian profile under certain conditions. The results of this paper provide further insight into the effect of the interaction pattern on self-organized motion for a Gaussian-type attractant/repellent nutrient profile in a swarm system.
This work was supported by NSFC (60274001, 10372002) and National Key Basic Research and Development Program (2002CB312200). Corresponding author: T. Chu. E-mail: chutg@pku.edu.cn.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Breder, C.M.: Equation descriptive of fish schools and other animal aggregations. Ecology 35, 361–370 (1954)
Arkin, R.: Behavior–Based Robotics. MIT Press, Cambridge (1998)
Lawton, J.R.T., Beard, R.W., Young, B.J.: A decentralized approach to formation maneuvers. IEEE Trans. Robot Automat. 19, 933–941 (2003)
Okubo, A.: Dynamical aspects of animal grouping: swarms, schools, flocks, and herds. Adv. Biophys. 22, 1–94 (1986)
Czirok, A., Stanley, H.E., Vicsek, T.: Spontaneously ordered motion of self-propelled particles. J. Phys. A: Math., Gen. 30, 1375–1385 (1997)
Toner, J., Tu, Y.: Flocks, herds, and schools: A quantitative theory of flocking. Phys. Rev. E 58, 4828–4858 (1998)
Gazi, V., Passino, K.M.: Stability analysis of swarm. IEEE Trans. Automat. Contr. 48, 692–697 (2003)
Chu, T., Wang, L., Mu, S.: Collective behavior analysis of an anisotropic swarm model. In: Proc. 16th Int. Symp. Math. Theor. Networks Syst.(MTNS 2004), Leuven, Belgium, July 2004, pp. 1–14 (2004) ) Paper ID: REG–345
Gazi, V., Passino, K.M.: Stability analysis of social foraging swarms. IEEE Trans. Syst. Man, and Cybernetics, Part B: Cybernetics 34, 539–557 (2004)
Liu, B., Chu, T., Wang, L., Wang, Z.: Swarm Dynamics of A Group of Mobile Autonomous Agents. Chin. Phys. Lett. 22, 254–257 (2005)
Khalil, H.: Nonlinear Systems, 2nd edn. Prentice–Hall, Inc., Upper Saddle River (1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, B., Chu, T., Wang, L. (2005). Collective Behavior Analysis of a Class of Social Foraging Swarms. In: Capcarrère, M.S., Freitas, A.A., Bentley, P.J., Johnson, C.G., Timmis, J. (eds) Advances in Artificial Life. ECAL 2005. Lecture Notes in Computer Science(), vol 3630. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11553090_59
Download citation
DOI: https://doi.org/10.1007/11553090_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28848-0
Online ISBN: 978-3-540-31816-3
eBook Packages: Computer ScienceComputer Science (R0)