  Human moving path is an important feature in architecture design. By studying
the path, architects know where to arrange the basic elements (e.g. structures,
glasses, furniture, etc.) in the space. This paper presents SimArch, a
multi-agent system for human moving path simulation. It involves a behavior
model built by using a Markov Decision Process. The model simulates human
mental states, target range detection, and collision prediction when agents are
on the floor, in a particular small gallery, looking at an exhibit, or leaving
the floor. It also models different kinds of human characteristics by assigning
different transition probabilities. A modified weighted A* search algorithm
quickly plans the sub-optimal path of the agents. In an experiment, SimArch
takes a series of preprocessed floorplans as inputs, simulates the moving path,
and outputs a density map for evaluation. The density map provides the
prediction that how likely a person will occur in a location. A following
discussion illustrates how architects can use the density map to improve their
floorplan design.
