Multi-agent-based simulation (MABS) is the processing of a multi-agent model of a complex system by a simulation platform that controls its execution. The objective is the understanding of the dynamic of this complex system with the experimenting of different configurations for the same multi-agent model. Following a scheduling process, an activated agent has to act according to his context, that is his current perceptible simulation state. In this paper, we propose to delegate the context computation process to the scheduling process. This approach has several advantages. The first is an optimization of the context computation, a single computation being used for several agents. The second advantage is a more configurable design process and a simplification of the reusability of agent behaviors in different simulations. The model that we propose gives a formal framework to support this context computation delegation while preserving agents’ autonomy. We describe a crisis situation to illustrate the benefits of our model and compare our approach with a classical simulation scheduling approach.