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

D.J. Thilakarathne

doi:10.1007/978-3-319-19066-2_9

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

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Abstract

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.

Original language	English
Pages (from-to)	84-94
Journal	Lecture Notes in Computer Science
Volume	9101
DOIs	https://doi.org/10.1007/978-3-319-19066-2_9
Publication status	Published - 2015
Event	28th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems - Seoul, South Korea Duration: 1 Jan 2015 → 1 Jan 2015

Bibliographical note

Proceedings title: Current Approaches in Applied Artificial Intelligence
Publisher: Springer
Place of publication: Seoul, South Korea

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10.1007/978-3-319-19066-2_9

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title = "A Neurologically Inspired Model of the Dynamics of Situation Awareness Under Biased Perception",

abstract = "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.",

author = "D.J. Thilakarathne",

note = "Proceedings title: Current Approaches in Applied Artificial Intelligence Publisher: Springer Place of publication: Seoul, South Korea; 28th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems ; Conference date: 01-01-2015 Through 01-01-2015",

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