Scale Transfer Modeling: Using Emergent Computation for Coupling an Ordinary Differential Equation System with a Reactive Agent Model

Abstract

This article deals with the coupling of analytical models with individual based models design with the reactive agents paradigm. Such a coupling of models of different natures is motivated by the need to find a way to model scale transfer in large complex systems, i.e. to model how low level of organization can be made to influence upper level and vice versa. This is a fundamental issue, and more particularly in ecological modeling where models are a real scientific tool of investigation. Individuals and populations are not described at the same scale of time and space but it is known that they act on each others. Based on this example, we model individuals in their environment and the population dynamics. While behavior is best modeled using an algorithmic framework (the reactive agent paradigm), population dynamics (because of the number of interacting entities) is best modeled using numerical models. We propose the use of the concept of emergent computation as a framework for coupling heterogeneous formalisms. In the same time, it is crucial to be aware of the consequences of the simplifications and of the choices that are made in the reactive agent model, such as the topology of space and various parameters. In this article, we discuss these issues and our approach on a case study drawn from marine ecology and we show that it is possible to find classical mathematical functional responses with a reactive agent system. Then, we propose a methodology to deal with the coupling of heterogeneous formalism useful in any kind of system modeling.

Modeling and simulation framework for value-based healthcare systems

“…A key issue in developing multi-perspective models is the validity of the bridging components, that is, the way parameters of a model are disaggregated using outputs of other models. Duboz et al 63 first asserted the need for awareness for such a legitimacy issue. If a parameter in one component varies in time according to the output of another component, then the status of the parameter changes, becoming a new type of state variable.…”

Emergence and complex systems: The contribution of dynamic graph theory

“…Coupling differential equations with a discrete-event logic is a difficult task that has been explored mainly by simulation specialists (e.g. Duboz et al, 2003). The concepts defined in this section and their relationships are shown in Figure 4 of the appendix.…”

Individual-Based Models for Public Health

“…Another interesting use of both approaches is to couple them to form a single model of the considered system at different space and timescales. Doing this, it is possible to simulate a scale transfer between two hierarchical levels, the individual level (IBM) and the population level (MFM) (Duboz et al, 2003). This coupling enables to study how individual behavior (foraging in the mentioned study) impacts the population dynamic.…”