Cognitive Models Of Decision Making Processes For Human-Robot Interaction

A fundamental aspect of human-robot interaction is the ability to generate expectations for the decisions of one\u27s teammate(s) in order to coordinate plans of actions. Cognitive models provide a promising approach by allowing both a robot to model a human teammate\u27s decision process as well as by modeling the process through which a human develops expectations regarding its robot partner\u27s actions. We describe a general cognitive model developed using the ACT-R cognitive architecture that can apply to any situation that could be formalized using decision trees expressed in the form of instructions for the model to execute. The model is composed of three general components: instructions on how to perform the task, situational knowledge, and past decision instances. The model is trained using decision instances from a human expert, and its performance is compared to that of the expert. © 2013 Springer-Verlag Berlin Heidelberg