Abstract (EN)

Multi-agent-based simulation (MABS) is used to understand complex real life processes and to experimentseveral scenarios in order to reproduce, understand and evaluate these processes. A crucial point in the designof a multi-agent-based simulation is the choice of a scheduling policy. In classical multi-agent-based simulationframeworks, a pitfall is the fact that the action phase, based on local agent context analysis, is repeatedin each agent at each time cycle during the simulation execution. This analysis inside the agents reducesagent flexibility and genericity and limits agent behavior reuse in various simulations. If the designer wants tomodify the way the agent reacts to the context, he could not do it without altering the way the agent is implementedbecause the link between agent context and agent actions is an internal part of the agent. In contrast toclassical approaches, our proposition, called EASS (Environment as Active Support for Simulation), is a newmulti-agent-based simulation framework, where the context is analyzed by the environment and where agentactivation is based on context evaluation. This activation process is what we call contextual activation. Themain advantage of contextual activation is the improvement of complex agent simulation design in terms offlexibility, genericity and agent behavior reuse.