The efficient simulation of multi-agent systems presents particular challenges which are not addressed by current parallel discrete event simulation (PDES) models and techniques. While the modelling and simulation of agents, at least at a coarse grain, is relatively straightforward, it is harder to apply PDES approaches to the simulation of the agents’ environment. In conventional PDES approaches a system is modelled as a set of logical processes (LPs). Each LP maintains its own portion of the state of the simulation and interacts with a small number of other LPs. The interaction between the LPs is assumed to be known in advance and does not change during the simulation. In contrast, the environment of a MAS is read and updated by agent and environment LPs in ways which depend on the evolution of the simulation. As a result, MAS simulations typically have a large shared state which is not associated with any particular agent or environment LP. In [1] we proposed a new approach to th...