  The contribution gives a micro-structural insight into the pedestrian
decision process during an egress situation. A method how to extract the
decisions of pedestrians from the trajectories recorded during the experiments
is introduced. The underlying Markov decision process is estimated using the
finite mixture approximation. Furthermore, the results of this estimation can
be used as an input to the optimization of a Markov decision process for one
`clever' agent. This agent optimizes his strategy of motion with respect to
different reward functions, minimizing the time spent in the room or minimizing
the amount of inhaled CO.
