Occupant behavior is widely regarded as one of the most significant sources of uncertainty in the prediction of building energy use. Preexisting simulation methods address this issue by automatically reproducing patterns of behavior found in historical occupant schedules. We extend these methods to incorporate spatial information. In our work, space layout influences the selection of individuals who participate in an activity, and the location where the activity occurs. Participants and locations are randomly selected based on probabilities derived from cost functions. One of these cost functions encourages participation between occupants of nearby workstations. Another discourages overcrowding. We apply the method to an existing office building to study how effectively an occupant model can be customized, and how accurately it can predict space utilization.