System Dynamics Modeling of Sensory-Driven Decision Priming

Abstract

The authors present an empirical investigation and a system dynamics model of human decision priming. Decision priming occurs when initial information creates the expectation that a given decision is appropriate, which speeds up or slows down decision making. A conjunction benefits-and-costs paradigm was used to collect the empirical data, whereas system dynamics techniques were used to create a computational model of decision priming. Decision priming occurred with simulated naturalistic stimuli (i.e., models of military tanks in a desert scene presented in perspective view), the results of which were modeled in a parallel-channels coactive architecture. Simulation revealed that the basic features of decision priming in humans could be simulated with this architecture. Decision priming likely occurs in naturalistic settings. Predictions derived from the model could provide useful information for the design of multimodal or multichannel displays.