Journal article

Collective behavior coordination with predictive mechanisms

  • Zhang, Hai-Tao Department of Engineering, University of Cambridge, United Kingdom - Department of Control Science and Engineering, Huazhong University mof Science and Technology, Wuhan, China
  • Chen, Michael ZhiQiang Department of Engineering, University of Leicester, United Kingdom
  • Stan, Guy-Bart Control Group of the Department of Engineering, Cambridge University, United Kingdom
  • Zhou, Tao epartment of Modern Physics, University of Science and Technology of China, Hefei, China - Department of Physics, University of Fribourg, Switzerland
  • Maciejowski, Jan M. Control Group of the Department of Engineering, Cambridge University, United Kingdom
Show more…
    2008
Published in:
  • IEEE Circuits and Systems Magazine. - 2008, vol. 6, no. 3, p. 67 - 85
English In natural flocks/swarms, it is very appealing that low-level individual intelligence and communication can yield advanced coordinated collective behaviors such as congregation, synchronization and migration. In the past few years, the discovery of collective flocking behaviors has stimulated much interest in the study of the underlying organizing principles of abundant natural groups, which has led to dramatic advances in this emerging and active research field. Inspired by previous investigations on the predictive intelligence of animals, insects and microorganisms, we seek in this article to understand the role of predictive mechanisms in the forming and evolving of flocks/swarms by using both numerical simulations and mathematical analyses. This article reviews some basic concepts, important progress, and significant results in the current studies of collective predictive mechanisms, with emphasis on their virtues concerning consensus improvement and communication cost reduction. Due to these advantages, such predictive mechanisms have great potential to find their way into industrial applications.
Faculty
Faculté des sciences
Department
Physique
Language
  • English
Classification
Physics
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/301033
Statistics

Document views: 4 File downloads:
  • zhou_cbc.pdf: 1