蜂群普适计算中的涌现与混沌分析

Dacheng Qu, H. Qu, Yu-shu Liu
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引用次数: 5

摘要

随着对普适计算和微机电系统的日益重视,需要将计算部署在非常小的设备上。这种受生物系统启发的系统中的合作与相互作用,由于其高度动态性、分散性和不可预测性的特点,似乎越来越复杂和难以想象。生物去中心化系统中的共同污名化特征是个体主体通过改变环境而间接与环境相互作用的重要过程。通过上下文感知,这些变化可以提高群体系统的出现,使其更连贯、适应性更强、更健壮。理解和利用涌现是研究和设计普适计算中全局一致行为的关键。本文描述了群体中耻感产生的羽化过程,并提出了对羽化问题有更深入认识的基本数学方法。结果表明,非线性动力学和混沌时间序列分析是一种很有前途的跨学科方法,可以为普适计算环境下突现的产生和控制提供见解
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emergence in swarming pervasive computing and Chaos Analysis
The growing emphasis on pervasive computing and MEMS requires the deployment the computation on very small devices for swarming system. The cooperation and interaction in such system inspired by biological system seem to be more and more complex and inconceivable because of highly dynamic, distributed and unpredicted features. The common stigmergy in biological decentralized system characterizes the important process that the individual agents indirectly interact with an environment by making changes to it. Through context-aware, these changes can raise the emergence that makes the swarming system more coherent, adaptive and robust. Understanding and exploiting emergence is key to study and engineer global coherent behavior in pervasive computing. This paper describes the process of emergence arisen from stigmergy in swarming, and present the fundamental mathematic method to gain more deeply insight of emergence. An experience was showed to prove that nonlinear dynamics and chaos time series analysis are one of the promising interdisciplinary methods that can provide the insights on producing and controlling emergence in pervasive computing environment
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