The emerging ”Computational Grid” infrastructure poses many new opportunities for the developing science of large scale multiagent simulation. The ability to migrate agent experiments seamlessly from simple, local single-processor development tools to large-scale distributed simulation environments provides valuable new models for experimentation and software engineering: first develop local, flexible prototypes, then as they become more stable progressively deploy and experiment with them at larger scales. Currently this kind of progressive scalability is hard for both practical and theoretical reasons: Practically, most agent platforms are designed for just one environment of operation. Smooth scalability is more than a matter of increasing agent numbers. Smooth scaling requires clear integration and consistent alignment between a variety of MAS system and simulation architectures and differing underlying infrastructures. This paper reports on recent progress with our experime...