Implementation logic refers to how the model uses existing theory or knowledge to create new knowledge. Deductive approaches use knowledge of the overall situation in order to predict outcome conditions. This includes models that have a formalized set of criteria, often with known weightings for the inputs, and for which existing algorithms are used to derive outcomes. Inductive approaches, on the other hand, are less straightforward, in that they try to generalize (often based upon samples of a specific data set) in order to derive more general models. While an inductive approach is useful if we do not know the general conditions or rules that apply to a specific domain, it is typically a trial and error approach that requires empirical testing to determine the parameters of each input variable. Most GISs have a limited range of tools for modelling. For complex models, or functions that are not natively supported in a GIS, external software environments are frequently used. In some cases, GISs and models can be fully integrated (known as embedded coupling) or linked through their data and interface (known as tight coupling). If neither is possible, the external model might run independently of a GIS; the model output should be exported into the GIS for further analysis and visualization. This is known as loose coupling.