  In the parable of Simon's Ant, an ant follows a complex path along a beach on
to reach its goal. The story shows how the interaction of simple rules and a
complex environment result in complex behavior. But this relationship can be
looked at in another way - given path and rules, we can infer the environment.
With a large population of agents - human or animal - it should be possible to
build a detailed map of a population's social and physical environment. In this
abstract, we describe the development of a framework to create such maps of
human belief space. These maps are built from the combined trajectories of a
large number of agents. Currently, these maps are built using multidimensional
agent-based simulation, but the framework is designed to work using data from
computer-mediated human communication. Maps incorporating human data should
support visualization and navigation of the "plains of research", "fashionable
foothills" and "conspiracy cliffs" of human belief spaces.
