Abstract. Using purely agent-based platforms for any kind of simulation requires to address the following challenges: (1) scalability (efficient scheduling of agent cycles is difficult), (2) efficient memory management (when and which data should be fetched, cached, or written to/from disk), and (3) modelling (no generally accepted meta-models exist: what are essential concepts, what just implementation details?). While dedicated professional simulation tools usually provide rich domain libraries and advanced visualisation techniques, and support the simulation of large scenarios, they do not allow for "agentization" of single components. We are trying to bridge this gap by developing a distributed, scalable runtime platform for multiagent simulation, MASeRaTi, addressing the three problems mentioned above. It allows to plug-in both dedicated simulation tools (for the macro view ) as well as the agentization of certain components of the system (to allow a micro view ). If no agent-related features are used, its performance should be as close as possible to the legacy system used
