Probabilistic Causality and Explications ((08) A02)

该项目将为基于因果关系的系统分析以及依赖于正式因果关系的解释的产生奠定基础。这种分析支持理解设计时系统组件之间的因果链和诱导的依赖级联，但也支持在运行时观察到的行为的似是而非的产生。该研究计划包括针对随机操作模型中不同形式的基于因果关系的推理的算法和复杂性理论问题。它将支持将从形式上解释观察的因果结构转移到直观地解释它们的视觉或语言表现形式。

The project will lay the foundations for a causality-based system analysis as well as the generation of explications that rely on formal cause-effect relations. This analysis supports the understanding of causal chains and of the induced cascades of dependencies between system components at design time, but also the generation of plausibilisations of observed behaviours at run-time. The research program includes algorithmic and complexity-theoretic problems for different forms of causality-based reasoning in stochastic operational models. It will support the transfer of causal structures explicating observations formally to visual or verbal representations explaining them intuitively.