Relaxing Synchronization Constraints in Distributed Agent-based Simulations

In the context of situated agents simulations, when the number of agents increases, the number of their interactions will be increased too. these growths leads to higher requirements in memory and computation power. when simulations involve millions of agents, it becomes necessary to distribute the simulator on a computer network. in this paper we study the impact of synchronization policies in such context. our claim is that when millions of agents are used in a simulation, because observations of these complex systems is made at the population level, emergent properties at the macroscopic level should not be highly impacted if some failure appears at the microscopic level. this paper is focused on the study of the impact of synchronization relaxation in the context of large scale situated agents simulations. we evaluate the cost in performance of several synchronization policies and their impact on the macroscopic properties of simulations. to that aims, we study three different time management mechanisms and evaluate them on two multi-agent applications.