Various situations in a massively multi-agent simulation will emerge in a simulation or the period of the simulation will become too long. These situations cause problems for system operators in that each action scenario becomes too complex to maintain and a simulation costs very long time. Therefore, flexible control of the simulation, such as changing simulation speed and switching agents' action scenarios, is required. We propose a meta-scenario description language and a meta-level control

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... rchitecture. The meta-scenario description language describes how to control simulations and agents based on an extended finite state machine. Meta-level control architecture achieves control on the basis of meta-scenarios provided by a meta-scenario interpreter, which controls interpreters of agents' action scenarios and the simulation environment. In addition, our proposed architecture does not lose scalability of massively multi-agent systems for some applications.