WEB-based Dynamic Social Networks (WDSN) Framework for Measurement-informed Decisionmaking under Uncertainty

我的研究计划汇集了基于web的动态社会网络（WDSN）分析和表征理论测量范畴理论和马尔可夫决策过程。WDSN与传统社交网络的不同之处在于，它们是蜂窝的、分布式的、基于网络的，因此规模更大、动态，并且可能包含不同程度的不确定性。本文的长期研究目标是：(1)如何对基于web的动态社会网络进行最佳建模，使其进化规律、时间进度、响应策略和自我修复等基本属性在模型中得到准确捕捉。(2)在整个WDSN演进过程中需要实现的测量目标是什么？必须定义一组用于描述WDSN目标的候选度量。在测量数据中可以区分测量误差和目标的模糊性两种不确定性。如何评估它们对测量过程的综合影响，以及评估对后续决策规则的合理影响？(3)在假设（即缺乏信息）不确定风险下，基于度量的决策规则是什么？(4)综合验证WDSN演化、基于测量的决策和自愈的合适方法和工具是什么？

My research proposal brings together web-based dynamic social networks (WDSN) analysis and representational theory of measurement within category theory and Markov decision processes. WDSN differ from traditional social networks in that they are cellular, distributed, web-based thus larger, dynamic, and may contain varying levels of uncertainty. The long term goals of my research deal with the following issues: (1) how to best model WEB-based dynamic social network so that its essential properties, such as evolution laws, time progress, response strategies and self-healing are precisely captured in the model? (2) what are the measurement goals that need to be achieved throughout WDSN evolution? A set of candidate metrics for describing the WDSN goals have to be defined. Two kinds of uncertainties - measurement errors and goals' fuzziness, can be differentiated in the measurement data. How to assess their combined effect on the measurement process and to assess the plausible effects on subsequent decision-making rules? (3) what are the rules for measurement-based decision-making under risk of uncertainty due to assumptions (that is, lack of information)? (4) what are the appropriate method and tools for an integrated validation of WDSN evolution, measurement-based decision making and self-healing?