A computable model for representing temporal knowledge and managing causality

We describe a new computable model for representing temporal information and for handling causality effectively. The proposed model permits qualitative temporal constraints (in which primitives can be points or intervals) and quantitative temporal constraints to be established. It also includes a representation of the causal constraints that are commonly found in any application domain. These causal constraints are represented in such a way as to broaden the habitual approach to handling causality, namely, by introducing the idea of subjective causality as a way of managing heuristic or private knowledge