Reusability and composability analysis for an agent-based hierarchical modelling and simulation framework

摘要

Agent-based modeling and simulation has been proved useful in a variety of different complex adaptive systems comprised of autonomous, interacting components. To resolve the shortcoming of current agent-based modeling frameworks with respect to decomposition and modularity, this paper presents a formal hierarchical modeling and simulation framework with three-level architecture to reduce ambiguity as well as improve clarity in the model definition. The bottom level is Component Model (CM), which implements some domain-specific support functionality, such as curve motion in the physical domain, intelligent decision-making in the cognitive domain, etc. The middle level is Agent Model (AM), which describes an agent which can react to the current situation by executing a sequence of CMs. The top level is System Model (SM), which defines that a CAS model consists of several AMs and also the interactions between these AMs. In the hierarchical architecture, one SM can be built up from lower-level models, which were linked in a loosely coupled fashion via an event-driven interface. We then analyze the reusability and composability of lower-level models of this hierarchical framework in a formalized way. To demonstrate the effectiveness of the proposed solution, we develop a graphical composite modelling tool named GraphSim, and the case study concerning two social dynamics system scenarios is also presented.