ABSTRACT
Neuroergonomics requires an understanding of both the system and the human in real work environments. Computational models can help us to make concrete predictions about complex and dynamic behaviors . This chapter describes MS/RPD, a nenrally-inspired, integrated modeling approach that represents the human and the system. MS stands for Micro Saint, a task network modeling tool. Task network modeling is a powerful and accessible way to represent systems but has difficulty representing the subtleties of the human in the system. RPD stands for Recognition Primed Decision (see Klein, 1 998), the inspiration for an underlying decision/cognitive model to augment task networks with simple and powerful leaming and memory mechanisms. MS/RPD was used to model the Three Block Challenge, a complex environment with pressured multi-attribute judgments . Because MSIRPD is computational, bottom-up, and neurally-inspired, i t marries computational power with efficiency, allowing models to be scaled up in size and complexity to represent problems of interest to the field of neuroergonomics .
