Adaptive hybrid agents for tactical decisions in pedestrian environments

This paper presents a hybrid agent architecture for modeling different types of decisions in a pedestrian simulation system. In particular, the present work focuses on tactical level decisions that are essentially related to the choice of a route to follow in an environment comprising several rooms connected by openings. These decisions are then enacted at the operational level by mean of a floor-field based model, in a discrete simulation approach. The described model allows the agent taking decisions based on a static a-priori knowledge of the environment and dynamic perceivable information on the current level of crowdedness of visible path alternatives. The paper presents the model formally, motivating the adopted choices with reference to the relevant state of the art. The model is also experimented in benchmark scenarios showing the adequacy in providing adaptiveness to the contextual situation.