期刊文献+

CONVERGENCE OF A CLASS OF MULTI-AGENT SYSTEMS IN PROBABILISTIC FRAMEWORK 被引量:9

CONVERGENCE OF A CLASS OF MULTI-AGENT SYSTEMS IN PROBABILISTIC FRAMEWORK
原文传递
导出
摘要 Multi-agent systems arise from diverse fields in natural and artificial systems, and a basic problem is to understand how locally interacting agents lead to collective behaviors (e.g., synchronization) of the overall system. In this paper, we will consider a basic class of multi-agent systems that are described by a simplification of the well-known Vicsek model. This model looks simple, but the rigorous theoretical analysis is quite complicated, because there are strong nonlinear interactions among the agents in the model. In fact, most of the existing results on synchronization need to impose a certain connectivity condition on the global behaviors of the agents' trajectories (or on the closed-loop dynamic neighborhood graphs), which are quite hard to verify in general. In this paper, by introducing a probabilistic framework to this problem, we will provide a complete and rigorous proof for the fact that the overall multi-agent system will synchronize with large probability as long as the number of agents is large enough. The proof is based on a detailed analysis of both the dynamical properties of the nonlinear system evolution and the asymptotic properties of the spectrum of random geometric graphs.
出处 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2007年第2期173-197,共25页 系统科学与复杂性学报(英文版)
基金 The research is supported by National Natural Science Foundation of China under the Grants No. 60221301 and No. 60334040.Acknowledgement The authors would like to thank Prof. Feng TIAN and Dr. Mei LU for providing the proof of Lemma 6 in Appendix B. We would also like to thank Ms. Zhixin Liu for valuable discussions.
关键词 CONNECTIVITY large deviation local interaction rules multi-agent systems random geometric graph spectral graph theory SYNCHRONIZATION Vicsek model 多Agent系统 同步 自动化系统 大偏差 局部相互作用
  • 相关文献

参考文献30

  • 1E. Shaw, Fish in schools, Natural History, 1975, 84(8): 40-46.
  • 2B. L. Partridge, The structure and function of fish schools, Sci. Amer., 1982, 246(6): 114-123.
  • 3A. Okubo, Dynamical aspects of animal grouping: Swarms, schools, flocks and herds, Adv. Biophys., 1986, 22: 1-94.
  • 4J.K.Parrish, S. V. Viscido, and D. Grunbaum, Self-organized fish schools: An examination of emergent properties, Biol. Bull., 2002, 202: 296-305.
  • 5T. Vicsek, A. Czirok, E. Jacob, I. Cohen, and O. Shochet, Novel type of phase transition in a system of self-deriven particles, Phys. Rev. Lett., 1995, 75(6): 1226-1229.
  • 6A. Czirok, A. Barabasi, and T. Vicsek, Collective motion of self propelled particles: Kinetic phase transition in one dimension, Phys. Rev. Lett., 1999, 82(1): 209-212.
  • 7C. W. Reynolds, Flocks, herds, and schools: A distributed behavioral model, in Comput. Graph. (ACM SIGGRAPH87 Conf. Proc.), 1987, 21: 25-34.
  • 8A. Jadbabaie, J. Lin, and A. S. Morse, Coordination of groups of mobile agents using nearest neighbor rules, IEEE Trans.Aurom. Control, 2003, 48(6): 988-1001.
  • 9W. Ren and R. W. Beard, Consensus seeking in multiagent systems under dynamically changing interaction topologies, IEEE Trans. Autom. Control, 2005, 50(5): 655-661.
  • 10A. Jadbabaie,On (tistributed coordination of mobile agents with changing nearest neighbors, Technical Report, University of Pennsylvania, Philadelphia, PA, 2003.

同被引文献34

引证文献9

二级引证文献67

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部