A framework for linking advanced simulation models with interactive cognitive maps

There is a dichotomy between advanced simulation models and flexible, simple tools for supporting policy-making. The former is difficult to use for policy-makers and the latter lacks in analytical value. It is a step forward to link these two types of tools in a way that enables the analytical value of the advanced models, while retaining the flexibility and comprehensibility of the simple tools. This paper presents a framework for such a linkage. The framework is based on an interactive cognitive mapping tool, which uses the qualitative probabilistic network (QPN) formalism to make qualitative (sign-based) calculations. This paper shows that there are several differences that need to be bridged. Each of these is discussed and approaches are presented. It is shown that (1) QPNs can be linked consistently to models with deterministic functions and continuous variables; (2) it is possible to deal with spatially and temporally explicit information; (3) despite the fact that QPNs must be a-cyclic, it is possible to capture feedback loops in a QPN-based tool. To prevent that negative feedback loops automatically result in ambiguous influences, we used a heuristic approach. The framework has been illustrated by analysing two models from literature with the QPN-based method.