A Neurologically Inspired Model of the Dynamics of Situation Awareness Under Biased Perception

This paper presents a computational cognitive agent model of Situation Awareness (SA), which is inspired by neurocognitive evidences. The model integrates bottom-up and top-down cognitive processes, related to various cognitive states: perception, desires, attention, intention, awareness, ownership, feeling, and communication. The emphasis is on explaining the cognitive basis for biased perception in SA, which is considered to be the most frequent factor in poor SA (the reason for 76% of poor SA errors), through perceptual load. A model like this will be useful in applications which relay on complex simulations (e.g. aviation domain) that need computational agents to represent human action selection together with cognitive details. The validity of the model is illustrated based on simulations for the aviation domain, focusing on a particular situation where an agent has biased perception.