In this work we formulate and propose an extended version of the multi-agent Swarm Grammar (SG) model for the generation of virtual worlds. It unfolds a comparatively small database into a complex world featuring terrain, vegetation and bodies of water. This approach allows for adaptivity of generated assets to their environment, unbounded worlds and interactivity in their generation. In order to evaluate the model, we conducted sensitivity analyses at a local interaction scale. In addition, at a global scale, we investigated two virtual environments, discussing notable interactions, recurring configuration patterns, and obstacles in working with SGs. These analyses showed that SGs can create visually interesting virtual worlds, but require further work in ease of use. Lastly we identified which future extensions might shrink required database sizes.