Abstract
In this paper, we investigate a weighted self-propelled particles system, wherein each agent’s direction is determined by its spatial neighbors’ directions with exponential weights concerning the neighbor numbers. In order to describe the fact that some agent with more neighbors might have much larger influence on its neighbors, we introduce a scaling exponent of the neighbor number between 0 and ∞. As the exponent increases, i.e., the effect of weight becomes stronger, the network of agents becomes much easier to achieve direction consensus in our simulation. Especially, when the exponent equals to 1, the convergence efficiency is enhanced.
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
Bonabeau, E., Dagorn, L., Fréon, P.: Scaling in animal group-size distributions. Proc. Natl. Acad. Sci. USA 96(48), 4472–4477 (1999)
Lorch, P.D., Gwynne, D.T.: Radio-telemetric evidence of migration in the gregarious but not the solitary morph of the Mormon cricket (Anabrus simplex: Orthoptera: Tettigoniidae). Naturwissenschaften 87(8), 370–372 (2000)
Shaw, E.: The Schooling of Fishes. American Scientist 206, 128–138 (1962)
Flierl, G., Grünbaum, D., Levins, S., Olson, D.: From Individuals to Aggregations: the Interplay between Behavior and Physics. Journal of Theoretical Biology 196(4), 387–454 (1999)
Shaw, E.: Fish in Schools. Natural History 84, 40–46 (1975)
Reynolds, C.: Flocks, herds and schools: a distributed behavioral model. Computer Graphics 21, 25–34 (1987)
Vicsek, T., Czirók, A., Ben-Jacob, E., Cohen, I., Shochet, O.: Novel Type of Phase Transition in a System of Self-Driven Particles. Physical Review Letters 75(6), 1226–1229 (1995)
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless senor networks: a survey. Computer Networks 38, 293–341 (2002)
Stipanovic, D.M., Inalhan, G., Teo, R., Tomlin, C.J.: Decentralized Overlapping Control of a Formation of Unmanned Aerial Vehicles. Automatica 40(8), 1285–1296 (2004)
Stilwell, D.J., Bishop, B.E.: Platoons of Underwater Vehicles. IEEE Control System Magazine 20(6), 45–52 (2000)
Jadbabaie, A., Lin, J., Morse, A.S.: Coordination of Groups of Mobile Autonomous Agents Using Nearest Neighbor Rules. IEEE Trans. on Automatic Control 48(6), 988–1001 (2003)
Ren, W., Beard, R.W.: Consensus Seeking in Multiagent Systems Under Dynamically Changing Interaction Topologies. IEEE Trans. on Automatic Control 50(5), 655–661 (2005)
Lin, Z., Broucke, M., Francis, B.: Local control strategies for groups of mobile autonomous agents. IEEE Trans. on Automatic Control 49(4), 622–629 (2004)
Grégoire, G., Chaté, H.: Onset of Collective and Cohesive Motion. Physical Review Letters 92(2), 40–46 (2004)
Huepe, C., Aldana, M.: Intermittency and Clustering in a System of Self-Driven Particles. Physical Review Letters 92(16), 168701–168704 (2004)
Aldana, M., Dossetti, V., Huepe, C., Kenkre, V.M., Larralde, H.: Phase Transitions in Systems of Self-Propelled Agents and Related Network Models. Physical Review Letters 98(9), 095702–168705 (2007)
Nagy, M., Daruka, I., Vicsek, T.: New aspects of the continuous phase transition in the scalar noise model (SNM) of collective motion. Physical A 373(9), 445–454 (2007)
Yang, W., Cao, L., Wang, X., Li, X.: Consensus in a heterogeneous influence network. Physical Review E 74(9), 037101–037104 (2006)
Li, W., Wang, X.: Adaptive velocity strategy for swarm aggregation. Physical Review E 75(9), 021917–021923 (2007)
Zhang, J., Zhao, Y., Tiana, B., Penga, L., Zhang, H.-T., Wang, B.-H., Zhou, T.: Accelerating consensus of self-driven swarm via adaptive speed. arXiv:/abs/0711.3896v1 (2007)
Watts, D.J., Strogatz, S.H.: Collective dynamics of ’small-world’ networks. Nature 393, 440–442 (1998)
Albert-L szl Barab si, ka Albert, R.: Emergence of Scaling in Random Networks. Science 286, 509–512 (1999)
András, C., Eugene, S.H., Tamás, V.: Spontaneously ordered motion of self-propelled particles. Physical A 30(9), 1375–1385 (1997)
Reebs, S.G.: Can a minority of informed leaders determine the foraging movements of a fish shoal? Animal Behaviour 59(2), 403–409 (2000)
Swaney, W., Kendal, J., Capon, H., Brown, C., Laland, K.N.: Familiarity facilitates social learning of foraging behaviour in the guppy. Animal Behaviour 63(3), 591–598 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Gao, Jx., Chen, Z., Cai, Yz., Xu, Xm. (2009). An Approach to Enhance Convergence Efficiency of Self-propelled Agent System. In: Zhou, J. (eds) Complex Sciences. Complex 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02469-6_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-02469-6_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-02468-9
Online ISBN: 978-3-642-02469-6
eBook Packages: Computer ScienceComputer Science (R0)