Representing and Analyzing Time and Causality in Hiqual models

Abstract

Interest in fertile representations of complex mechanisms is widely increasing. For a variety of reasons many present AI-systems either anticipate or already have a desperate need for a deeper understanding of their respective domains of discourse. HIQUAL is both a representation language and a tool for the analysis of the structure and behavior of complex systems. Individual components may be arranged horizontally as a set of highly modular, communicating model instantiations, designed to represent one level of abstraction. Separated from the individual models, vertical relations between models at different levels of abstraction allow for the formation of hierarchical representations. This paper focuses on the temporal and causal analysis of HIQUAL models. The presentation is mainly based on a simple bat detailed example.