Many models are developed within a particular modelling paradigm (using the term paradigm in the dictionary sense of “a conceptual framework within which scientific theories are developed”). Thus, a particular model might be described as differential equation model, a System Dynamics model, an age-class model, a spatial model, a cellular automaton model, an object-oriented model, or an agent-based model. Some large-scale ecosystem models do combine two or more paradigms, but these tend to be implemented as large, unwieldy programs.
One of the strands that led to the development of Simile was to explore the extent to which all (or as many as possible) modelling paradigms could be handled within a single, easy-to-use visual modelling environment. This does not mean that each one has its own identity within Simile. Rather, it means that each one can be readily recast to fit within Simile's model-design language. To a large extent, this is now possible: one model can have parts that are simple System Dynamics, other parts which are disaggregated into spatial elements or age-classes, and other parts that involve dynamically-varying populations of objects — all interacting with each other. The section on modelling approaches discusses these in detail.
Nevertheless, we are not claiming that Simile can handle all modelling paradigms. Areas that we wish to develop in the future include qualitative and rule-based modelling, multi-agent system modelling, and certain forms of within-model optimisation.