| Abstract |
Human awareness under different circumstances is complex and non-trivial to understand. Nevertheless, due to the importance of awareness for safety and efficiency in many domains (e.g., the aviation domain), it is necessary to study the processes behind situation awareness, to eliminate possible errors in action selection that may lead to disasters. This talk discusses a computational cognitive agent model for situation awareness from the perspective of action selection, 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, (prior and retrospective) awareness, ownership, feeling, and communication. Based on the model, various cognitive effects can be explained, such as perceptual load, predictive processes, inferential processes, cognitive controlling, unconscious bias, and conscious bias. A model like this will be useful in domains that benefit from complex simulations (e.g. the aviation domain). |