  A mesoscopic approach to modeling pedestrian simulation with multiple exits
is proposed in this paper. A floor field based on Qlearning Algorithm is used.
Attractiveness of exits to pedestrian typically is based on shortest path.
However, several factors may influence pedestrian choice of exits. Scenarios
with multiple exits are presented and effect of Q-learning rewards system on
navigation is investigated
