Humans are more successful in planning collision-free trajectory with mutual avoidance manoeuvres in a populated environment than any motion planning algorithm so far. While humans easily can deal with predict the motion of surrounding people, robotics systems are still encountering problems. For this reason, we want to improve the robot navigation starting from the study of humans decisions. The majority of the approaches concentrate their attentions to predict the motion of agents individually without considering the interaction between humans. Thus, we model the motions of humans considering the interactivity of pedestrians in the presence of multiple agents using game-theoretic approach. The game theory has a lot of advantages over the reactive method, in fact can model the mutual anticipation of the influence of other agents and adapt the own decisions based on the possible actions of others.