计算机科学 ›› 2010, Vol. 37 ›› Issue (8): 182-185.

• 软件工程 • 上一篇    下一篇

动态随机影响图建模方法

赵新,李群,朱一凡   

  1. (国防科技大学信息系统与管理学院系统工程系 长沙410073)
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金项目(60974073,60974074),装备预研基金课题(9140C640505)资助。

Dynamic-stochastic Influence Diagrams for Decision Analysis

ZHAO Xin,LI Qun,ZHU Yi-fan   

  • Online:2018-12-01 Published:2018-12-01

摘要: 通过引入时间片的概念和反馈特性,时间片影响图增强了经典影响图描述因果影响关系网络的能力,但仍不足以支撑对复杂系统/体系问题中并发、交互、协同等过程的有效描述。参考离散事件系统建模的相关特性及方法,通过增加一个时间变量节点并扩展现有的模型规范,提出了一种动态随机影响图建模方法;详细说明了该方法的图形化语法、语义,并给出了其模型节点逻辑关系的迭代演算算法。该方法较完整地保持了典型时间片影响图的现有特性,可以作为改进现有方法的折中方案,以描述决策问题中的复杂行为过程。

关键词: 决策分析,时间片影响图,离散事件系统仿真,动态随机影响图,模型规范,迭代解算

Abstract: As an expanded mode of Influence Diagrams,the himcSliced IDs (TSIDs,or Dynamic IDs) increases cause effect relationship description capability effectively for decision analysis. But it still can't becomingly describe intercurrent, alternating, or coordinated processes of complex system. Based on the analysis of discrete-event system model, the paper suggested a Dynami}stochastic IDs (DSIDs) by introducing a time node to expand existing model-criterion, explicated its graphical syntax,and gave its evaluating algorithm The DS)Ds could be used as an effected approach to improve existing himcSliced IDs to describe complex processes.

Key words: Decision analysis, Time-sliced influence diagrams, Discrete-event system simulation, Dynami}stochastic in flucnce diagrams, Model-criterion, Model evaluating

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