Collective Behavior Coordination with Predictive Mechanisms

被引:73
作者
Zhang, Hai-Tao [1 ,2 ]
Chen, Michael ZhiQiang [1 ,3 ]
Stan, Guy-Bart [1 ]
Zhou, Tao [4 ,5 ]
Maciejowski, Jan M. [1 ]
机构
[1] Univ Cambridge, Dept Engn, Cambridge CB2 1PZ, England
[2] Huazhong Univ Sci & Technol, Dept Control Sci & Engn, Wuhan 430074, Peoples R China
[3] Univ Leicester, Dept Engn, Leicester LE1 7RH, Leics, England
[4] Univ Sci & Technol China, Dept Modern Phys, Hefei 230026, Peoples R China
[5] Univ Fribourg, Dept Phys, CH-1700 Fribourg, Switzerland
基金
中国国家自然科学基金; 高等学校博士学科点专项科研基金; 英国工程与自然科学研究理事会;
关键词
D O I
10.1109/MCAS.2008.928446
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:67 / 85
页数:19
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